Engg-Electrical

Research area: AI, ML, Systems, Programming Languages, Hardware/Software Interfacing

Student roles:
Design, Development, Presentation, and Reporting

Skills required:
Programming knowledge, AI/ML Knowledge, Hardware/Software Interfacing

Research area: My specialized research focuses on AI-enabled microwave and RF sensing systems for harsh-environment applications. My work integrates electromagnetic design, edge intelligence, advanced materials, and sensor fusion to develop lightweight, low-power, and highly reliable sensing platforms. I investigate microwave sensors and antennas for environmental monitoring, structural health assessment, ice detection, and autonomous systems operating under extreme conditions. My research also explores additive manufacturing and multilayer conductive materials for scalable, cost-effective RF devices with enhanced performance, supporting next-generation aerospace, industrial, and intelligent sensing applications.

Student roles:
The student will play an active role in the research, development, and experimental validation of AI-enabled microwave sensing technologies for harsh-environment applications. The role involves contributing to multiple stages of the project, including electromagnetic design, numerical simulation, hardware prototyping, embedded system integration, data analysis, and performance evaluation of microwave and RF sensing platforms.
The student will assist in designing and optimizing microwave sensors, antennas, and RF components using electromagnetic simulation tools such as CST Microwave Studio, HFSS, ADS, or equivalent platforms. Responsibilities include analyzing sensor behavior under varying environmental conditions such as ice accumulation, humidity, temperature variation, and mechanical stress, as well as evaluating sensing accuracy, reliability, and robustness.

The student will also support the integration of edge computing and AI algorithms into the sensing framework. This may involve signal processing, feature extraction, machine learning model development, and implementation of lightweight AI methods for real-time environmental monitoring and classification tasks. Additional activities may include programming in MATLAB, Python, or embedded platforms for data acquisition and system control.

Experimental work is an important component of the role. The student will participate in prototype fabrication, laboratory measurements, calibration, and testing of sensing systems using microwave/RF instrumentation. Exposure to additive manufacturing techniques, PCB prototyping, and advanced conductive materials may also be included depending on project requirements.
Beyond technical contributions, the student will engage in literature review, technical documentation, preparation of research reports and presentations, and collaboration with graduate students and researchers in a multidisciplinary environment. The role is intended to provide hands-on experience in microwave engineering, AI-assisted sensing, and intelligent embedded systems while contributing to the development of next-generation resilient sensing technologies for aerospace, industrial, and autonomous applications.

Skills required:
The student should have a strong background in electrical engineering, physics, or a related field, with knowledge of electromagnetics, microwave/RF systems, antennas, or signal processing. Experience with simulation tools such as CST, HFSS, ADS, MATLAB, or Python is highly desirable. Familiarity with embedded systems, machine learning, edge AI, or sensor integration would be an asset. The student should possess strong analytical and problem-solving skills, the ability to work independently and collaboratively in a multidisciplinary research environment, and effective technical communication skills. Experience with prototyping, PCB design, or additive manufacturing is considered beneficial but not mandatory.

Research area: Dr. Chen’s research focuses on AI-enabled next-generation wireless communication, sensing, and networking systems. His work spans advanced communication technologies, including integrated sensing and communication, millimeter-wave and near-field communications, wireless power transfer, RFID, MIMO, OFDM, OTFS, channel estimation, signal detection, beamforming, multiple access, and wireless resource management. He also investigates intelligent radar signal processing for high-resolution 3D imaging, target detection and localization, environment perception, and radio-based mapping. In addition, his research develops AI-driven autonomous wireless networks and distributed optimization methods, including generative AI, large language models, foundation models, reinforcement learning, federated learning, multi-agent learning, distributed resource allocation, and decentralized network control.

Student roles:
The intern will actively participate in research activities related to integrated sensing and communication (ISAC) systems in the Intelligent Communications, Networking, and Computing (ICNC) Laboratory. Under the supervision of Dr. Chen and with mentoring support from graduate students, the intern will review relevant literature, learn the necessary theoretical and technical background, contribute to the refinement of research ideas, and assist in formulating mathematical models and optimization problems. The intern will help develop and implement algorithms for efficient wireless resource allocation, including transmit power, spectrum, antenna beams, and user association, with the goal of balancing communication performance, sensing accuracy, energy efficiency, and system reliability. The work may also involve exploring generative AI and learning-based methods to support adaptive decision-making in dynamic ISAC environments. The intern is expected to conduct simulations, analyze numerical results, prepare figures and technical summaries, actively participate in regular group meetings and research discussions, and contribute to the preparation of research manuscripts for potential publication.

Skills required:
The intern is expected to have a solid background in electrical or computer engineering, or a closely related field. Prior coursework in linear algebra, probability theory, advanced mathematics, and programming is required. Experience with communication systems, radar systems, optimization theory, artificial intelligence, MATLAB, or Python would be an asset. The intern should also have strong mathematical and analytical skills, self-motivation, and a willingness to learn AI-driven optimization and learning methods for advanced wireless communication and networking systems during the project.

Research area: Dr. Chen’s research focuses on AI-enabled next-generation wireless communication, sensing, and networking systems. His work spans advanced communication technologies, including integrated sensing and communication, millimeter-wave and near-field communications, wireless power transfer, RFID, MIMO, OFDM, OTFS, channel estimation, signal detection, beamforming, multiple access, and wireless resource management. He also investigates intelligent radar signal processing for high-resolution 3D imaging, target detection and localization, environment perception, and radio-based mapping. In addition, his research develops AI-driven autonomous wireless networks and distributed optimization methods, including generative AI, large language models, foundation models, reinforcement learning, federated learning, multi-agent learning, distributed resource allocation, and decentralized network control.

Student roles:
The intern will actively participate in research activities related to intelligent radar sensing and environmental map reconstruction in the Intelligent Communications, Networking, and Computing (ICNC) Laboratory. Under the supervision of Dr. Chen and with mentoring support from graduate students, the intern will review relevant literature, learn the necessary theoretical and technical background, contribute to the refinement of research ideas, and assist in formulating signal processing and data analysis problems for radar-based environmental sensing.

The intern will help develop and implement algorithms for radar data processing, feature extraction, scene understanding, and environmental map reconstruction. The work may involve processing simulated or measured radar sensing data, analyzing signal characteristics, addressing challenges caused by noise, multipath propagation, limited resolution, and dynamic environments, and exploring AI-enabled methods for improving sensing accuracy and mapping reliability. Relevant approaches may include digital signal processing, optimization, machine learning, deep learning, and generative AI-based modelling.

The intern is expected to conduct simulations, analyze numerical results, prepare figures and technical summaries, actively participate in regular group meetings and research discussions, and contribute to the preparation of research manuscripts for potential publication.

Skills required:
The intern is expected to have a solid background in electrical engineering, computer engineering, computer science, or a closely related field. Prior coursework in linear algebra, probability theory, advanced mathematics, and programming is required. Experience with radar systems, signal processing, sensing systems, optimization theory, artificial intelligence, MATLAB, or Python would be an asset. The intern should also have strong mathematical and analytical skills, self-motivation, and a willingness to learn AI-driven signal processing, radar data analysis, and environmental map reconstruction methods during the project.

Research area: Researcher with decades of experience (private sector and government) in applied and experimental science, focusing on control, sensing and autonomous systems. See resume for additional information.

Student roles:
The intern may contribute to one or more of the following activities:
(1) help develop a system of acoustic arrays capable of localizing an acoustic source;
(2) evaluate a few algorithms and assess their performance under various conditions;
(3) contribute to ongoing research project(s);
(4) write code (Python or Matlab) and summary reports;
(5) contribute to mathematical development whether in signal processing or control.

The importance of the above roles may be adjusted to meet the intern's school requirements or career aspirations.

Skills required:
The ideal intern can:
(1) can work in teams;
(2) has programming skills;
(3) is an autonomous thinker, resourceful, and strong at problem-solving;
(4) has an analytical approach to problem-solving;
(5) has strong mathematical training;
(6) has potential interests in pursuing graduate education (master's, etc.);
(7) able to read, write and understand documents written in English;

Interns with only a few of the attributes listed above will also be considered. Please clearly indicate which one(s) of those attributes apply to you.

Research area: The rapid expansion of data-intensive technologies, including artificial intelligence, immersive communication, and the Internet of Everything, is driving wireless systems toward terabit-per-second operation. While 5G has enabled major advances, its bandwidth is insufficient to meet future demands. Consequently, the terahertz (THz) spectral range (100 GHz–1 THz) is emerging as a key enabler for beyond-5G and 6G communication systems. Unlocking this regime requires the development of advanced physical-layer components capable of dynamically controlling THz wave propagation. In particular, reconfigurable waveguiding platforms incorporating active materials are critical for achieving adaptive and efficient THz signal processing.

Student roles:
The student will engage in both computational and experimental aspects of THz photonics, working closely with PhD students and postdoctoral researchers. The student will gain expertise in metamaterial-based device design, THz characterization techniques, and data analysis. The main tasks include:
- Perform electromagnetic simulations of metamaterial unit cells and hybrid THz waveguide structures to evaluate their transmission and spectral response.
- Assist in the experimental characterization of fabricated devices using THz time-domain spectroscopy (THz-TDS).
- Support the fabrication and integration of flexible metamaterial overlays onto THz waveguides, including exposure to thin-film processing and transfer techniques.
- Analyze and compare simulated and experimental results, and contribute to device optimization and reporting.

Skills required:
The ideal candidate will have a background in physics, electrical engineering, photonics, or a closely related field, with a solid understanding of electromagnetic wave propagation. Experience in numerical modelling of electromagnetic systems is preferred, and familiarity with simulation tools such as CST Microwave Studio, COMSOL Multiphysics, or Lumerical will be advantageous. Basic programming skills (MATLAB or Python) are expected. The candidate should be highly motivated, detail-oriented, and capable of working effectively in a collaborative research environment. Senior undergraduate and graduate students with a strong interest in THz photonics and metamaterials are encouraged to apply.

Research area: Advanced power electronics, energy systems, and digital technologies for next-generation AI data centers. Research focuses on high-efficiency power conversion, medium-voltage and DC power distribution architectures, battery energy storage integration, thermal management, reliability, and real-time simulation. The objective is to develop sustainable, resilient, and grid-friendly power infrastructures capable of supporting rapidly growing AI computational demands while minimizing energy consumption and environmental impact.

Student roles:
The student will conduct literature reviews, develop simulation models, analyze technical data, and evaluate the performance of advanced power-electronics architectures for AI data centers. Responsibilities include implementing simulation studies, documenting results, participating in research meetings, preparing technical reports, and contributing to scientific publications and presentations. The student will work closely with graduate researchers and gain exposure to state-of-the-art power-electronics and energy-system research.

Skills required:
Candidates should have a background in electrical engineering, power electronics, energy systems, or a related discipline. Knowledge of circuit analysis, electric power systems, and control systems is desirable. Experience with MATLAB/Simulink, Python, PSCAD, or similar engineering software is beneficial but not required. Strong analytical, programming, and problem-solving skills are preferred. Motivated undergraduate students interested in sustainable energy technologies, AI infrastructure, and advanced power systems are encouraged to apply.

Research area: Terahertz (THz) spectroscopy and ultrafast laser science. We conduct experiments using the Advanced Laser Light Source, which houses a cluster of various intense femtosecond Ti:sapphire lasers with different energy and repetition rates, ranging from 5 mJ, 5 kHz to 5 J, 10 Hz. We also operate an Advanced THz Technology Lab with numerous setups for THz spectroscopy, microscopy and imaging.

Student roles:
The student will first receive a course in laser safety from the staff at the INRS. Then, the student will work with the postdoctoral fellows and graduate students in the group to learn the basics of femtosecond laser systems and THz techniques, and particularly in methods of THz generation and detection. The student will be asked to perform THz measurements of a specific sample (such as algal toxins and viruses), which will be determined upon discussions within the group. The student will then be asked to analyze the data, and then to write a report. Moreover, the photonics melting pot at the INRS will provide the students unparalleled opportunity to work and interact with world-class researchers working in all areas of laser physics.

Skills required:
Strong scientific curiosity and motivation for research are the absolute requirements of the candidate. Knowledge in optics and/or solid-state physics will be assets.

Research area: My research focuses on intelligent communication and networking systems for B5G/6G networks. Areas of interest include intelligent IoT systems, semantic communications, multi-access edge computing (MEC), edge intelligence, digital twin-assisted networking, joint communication-computing resource management, and AI-native network automation. Our team investigates the integration of machine learning, generative AI, large language models, and agentic AI into wireless networks to enable autonomous, efficient, and resilient network operation. The goal is to develop scalable and intelligent network architectures that support future connected, data-driven, and service-oriented applications.

Student roles:
The student will play an active role in the design, development, and evaluation of an Agentic AI-assisted Digital Twin framework for next-generation 6G networks. The project will provide hands-on research experience spanning wireless communications, digital twins, artificial intelligence, and network automation.

The student will begin by conducting a comprehensive literature review on digital twin technologies, agentic AI, network intelligence, and autonomous network management. Based on this review, the student will contribute to the development of digital twin models that accurately represent communication network environments and support real-time monitoring and prediction.

The student will assist in the design and implementation of Agentic AI algorithms that enable autonomous perception, reasoning, planning, decision-making, and self-correction within the digital twin ecosystem. The student will also develop simulation platforms and experimental scenarios to evaluate the proposed framework under diverse network conditions.

Additional responsibilities include conducting simulations and performance evaluations, collecting and analyzing experimental data, comparing the proposed methods with existing approaches, and identifying opportunities for further improvement. The student will participate in regular research meetings, collaborate closely with the research team, and contribute to the preparation of technical reports, research publications, and project presentations.

Through this project, the student will gain valuable experience in digital twin-assisted networking, AI-native network automation, machine learning, agentic AI, wireless communications, scientific research methodologies, and technical communication skills.

Skills required:
We welcome highly motivated students with strong interests in the above research areas to join our team and contribute to high-impact research. Applicants should have a background in Communications Engineering, Computer Science, or related fields, with an undergraduate GPA of at least 3.3. Strong analytical skills, solid mathematical foundations, programming proficiency (e.g., MATLAB, Python), and effective communication and teamwork skills are essential.

Research area: My research program focuses on the application of a variety of ultrafast imaging and spectroscopic techniques to complex materials - especially to quantum materials. A combination of visible, near-infrared, and THz spectroscopy are used to probe electronic and magnetic dynamics while complementary ultrafast microscopes are being developed to provide imaging of the same phenomena.

Student roles:
Students working on this project will work with other students in the host research group to develop a new software framework that includes control and analysis software for a variety of ultrafast optical instrumentation. The student(s) will be principally responsible for the creation of the new software framework but will work with the support of graduate students who's projects are related to the instrumentation and will benefit from the new framework. This will allow the Mitacs GlobalLink students to gain insight and experience from peers with expertise in the instrumentation while also getting support for learning and implementing different analysis techniques. The students will also have the opportunity to be trained in and assist with data acquisition to gain hands on experience with ultrafast optical instrumentation.

Skills required:
The successful student should have a strong background in analysis using scientific python and experience creating small applications. The successful student should also have a strong background in physics with emphasis on optics and condensed matter physics. A collaborative and teamwork focused attitude is a significant asset as is a general curiosity driven attitude towards overcoming significant scientific challenges.

Research area: Wireless communications, signal processing, large intelligent surface, MIMO communications, detection and estimation, performance analysis.

Student roles:
Mathematical modelling and analysis, numerical simulation, report writing.

Skills required:
Strong background in linear algebra, mathematical analysis, and probability theory. Basic knowledge of communications.

Research area: High-order harmonic generation, attosecond science and THz spectroscopy. We conduct experiments at the Advanced Laser Light Source, which houses a cluster of various intense femtosecond Ti:sapphire lasers with different energy and repetition rates, ranging from 5 mJ, 5 kHz to 5 J, 10 Hz.

Student roles:
The students will first receive a course in laser safety from the staff at the Advanced Laser Light Source (ALLS). Then, the students will work with the postdoctoral fellows and graduate students in the group to learn the basics in femtosecond laser systems and optical techniques, and particularly in methods of high-order harmonic generation. The students will then be asked to analyze the data, and then use the simulation code developed at the INRS to simulate the experimental observations. Moreover, the photonics melting pot at ALLS will provide the students unparalleled opportunity to work and interact with world-class researchers working in all areas of laser physics.

Skills required:
Strong scientific curiosity and motivation for research are the absolute requirement of the candidate. Knowledge in optics and/or solid-state physics will be assets.

Research area: In just five days, OpenAI’s ChatGPT, which utilizes state-of-the-art Large Language Models (LLMs), gained a user base of over one million individuals. One of the key features of ChatGPT is its ability to understand and answer open-ended questions about any topics. Now it has been seen that AI aids have been available on various software tools (e.g., Google Colab-AI). With abundant promising potential in revolutionizing various fields, LLMs herald a new future.

Student roles:
The student will work with my graduate (mostly PhD) students in a team

Skills required:
Python programming, circuit simulation

Research area: My research group is working on advancing the control system technologies and their applications to various engineering systems, such as robotics, mechatronics, and industrial processes, with social impacts and public benefits. The current research focus is on developing new control and optimization frameworks for autonomous robotic vehicle (ARV) systems. The challenges and opportunities of incorporating advanced optimization techniques (e.g., machine/deep learning) into ARV sensing, navigation, and control system design will be fully investigated. The developed new technology will be applied to enable interesting applications such as vision servoing, autonomous driving, multi-robot cooperative control, etc.

Student roles:
The student will participate in multiple steps involved in the development of autonomous driving system. The main role of the student will be to assist (graduate students) in implementing the selected mapping, localization, planning or control algorithms on an existing scale vehicle and in the simulator, conducting experiments, collecting experimental data, analysing some of the data, and writing a report. It is important to note that we will tailor the tasks to the background of the student. For example, if the student has strong software design skills, they might contribute to the creation of a digital twin in the simulation environment for fast experimentation; Or if the student has hardware design skills, they might contribute to the design and integration of the additional sensors to the vehicle platform; Or if the student is strong in mathematics (with a good understanding of control system and numerical optimization), they might contribute to the modeling of the time optimal control problem and to the development of novel planning and control algorithms. In addition, the student will read and discuss a few academic papers/textbooks to better understand the research topic. Overall, the student will have the opportunity to participate in an exciting robotics project, experience research, learn new knowledge and skills, collaborate with graduate students, and obtain mentorship.

Skills required:
The student needs to have undergraduate-level knowledge of feedback control systems, and have programming skills in Python, C/C++, or MATLAB. The students are preferred to have ONE or more of the following skills: knowledge of mathematical optimization, (formal) software design experiences, software design skills, computer vision, artificial intelligence (AI), or hardware design skills. The selected research intern will likely have an engineering, computer science, or mathematics background to fulfill the requirements above. The ideal candidate should be resourceful, enthusiastic, organized, reliable and communicate well. The student must work well with other students: the student will work with a graduate student

Research area: My research interests are dynamics, control, and motion planning of robotic and autonomous systems with focus on intelligent manufacturing and industrial applications. This includes, but is not limited to, unmanned aerial vehicles, spacecraft, space mechanisms, and robotic manipulators. My research work encompasses a broad spectrum, ranging from dynamics modeling for complex systems, robust controller design, machine learning and AI, trajectory optimization, vibrations, contact mechanics, mechanical design and stress analysis, energy-saving controllers and trajectories, and testing and validation.

Student roles:
The student will collaborate closely with a graduate student on dynamics modeling and controller design for robotic manufacturing tasks. Student's responsibilities include:
(1) Conducting literature review and identifying research gaps.
(2) Developing and implementing machine learning and AI algorithms for defect detection, classification, and localization.
(3) Using onboard sensors, such as cameras, depth sensors, and LiDAR, to acquire and process inspection data.
(4) Designing and evaluating autonomous scanning strategies to ensure complete object coverage under varying orientations and positions.
(5) Integrating perception and sensing algorithms with robotic systems for automated inspection and decision-making.
(6) Running simulations to evaluate these algorithms, strategies, and techniques.
(7) Experimentally validating controllers on industrial robots.
(8) Summarizing results in a report, with potential to co-author a publishable research paper.

The student will gain hands-on experience with modeling, control design, simulation, experimentation, and technical reporting. The student will learn to work collaboratively in an interdisciplinary and supportive research environment and develop skills essential for robotics research and industrial applications.

Skills required:
The student should meet at least three of the following:
(1) background in mechanical, electrical, mechatronics, robotics, control, manufacturing, or autonomous systems;
(2) background in machine learning, reinforcement learning, and/or AI;
(3) strong mathematics foundation;
(4) programming skills in Python and/or MATLAB/Simulink (low level programming, e.g., C++, is an asset);
(5) experience with vision systems is an asset.

Hands-on robotics experience is a plus. Students must be team-oriented, value diversity, and be available full-time for the internship.

Research area: Research at the Human-Robot Interaction lab of the University of Calgary primarily aims to make human-robot interactions safe, comfortable, and intuitive. Research on physical interactions between humans and robots, however, cannot happen without robots designed to safely operate around humans. We are currently working on developing a robot that can pick up and place objects on shelves, within a public space.

Student roles:
Your task will be to design and test software that enable a robot to locate and identify specific items on a shelf.

Skills required:
- Prior knowledge of linear algebra, programming (Python and/or C++), instrumentation, measurements, signal processing and system analysis will be of great help to complete this project.
- Knowledge of computer vision, machine learning, and/or RFID systems would be advantageous.
- Teamworking skills are essential, as you will be working on this project with other students.

Research area: The NeuroCognitive Imaging Lab (NCIL) conducts basic and applied cognitive neuroscience research. Much of our research is focused on language and neuroplasticity — how the brain changes with experience. The ultimate goal of our work is to help people live healthier, happier, and more productive lives. Our research primarily uses EEG neuroimaging, combined with data analysis pipelines written largely in Python that include conventional signal processing, machine learning, and AI. Current projects in the lab are focused on brain computer interface development, second language acquisition, reading development in children, and hyperscanning studies of pairs of individuals engaged in conversation.

Student roles:
Become familiar with necessary background literature for the project
- Become familiar with the codebase for the game and signal processing/classification pipeline
- Make improvements as directed to the codebase. May include refinements to stimulation protocols, additional game levels, feedback, signal processing, ML
- Follow best practices in version control and documentation
- Test the software with human users, including EEG recording
- Perform offline analysis of classification data and game metrics
- At the end of internship, prepare a written summary of the work and report a summary to the lab group in an oral presentation

Skills required:
Essential skills:
- Python programming
- signal processing
- machine learning
Desired skills:
- experience with EEG data collection
- experience with EEG data processing
- embedded systems programming
- Edge ML/AI implementations

Research area: Mohamed Lamine Fayçal Bellaredj a obtenu le diplôme d'ingénieur en électronique et le magister en physique de l'Université des Sciences et Technologies d'Oran (USTO), Bir El Djir, Algérie, respectivement en 2005 et 2007, ainsi que le doctorat. diplôme en micro-ingénierie de l'Université de Franche-Comté, Besançon, France, en 2013. Ses intérêts de recherche incluent l'acoustofluidique, les ondes acoustiques de surface et les dispositifs acoustiques à base de métamatériaux, l'ingénierie passive embarquée pour l'électronique RF, numérique et de puissance, l'hybride flexible. électronique (FHE), micro-ingénierie/nano-ingénierie, modélisation, fabrication et caractérisation de systèmes MEMS/nanoélectromécaniques (NEMS), physique et technologie des dispositifs à semi-conducteurs et cellules solaires

Student roles:
Revue bibliographique
Conception et fabrication
Rédaction de rapports et de publications (encouragée)

Skills required:
Formation en ingénierie électrique, sciences des matériaux, physique etc.

Research area: Development of radio frequency (RF) energy harvesting systems, antennas, rectifiers, and wireless power solutions for self-powered sensing and Internet of Things (IoT) applications. Research activities include ambient RF energy harvesting, wearable and embedded wireless systems, energy-aware sensor platforms, and the characterization of electronic devices operating under ultra-low-power conditions

Student roles:
The student will play a key role in establishing a device characterization framework to support ongoing RF energy harvesting research within the Wireless Power, Instrumentation, Radar, Electromagnetics, Sensors and Systems (WIRELESS) Research Group. Working under the supervision of the research team, the student will identify, evaluate, and experimentally characterize commercially available low-power electronic devices that have the potential to operate using harvested RF energy.

The project will begin with a literature review and market survey to identify candidate devices including environmental sensors, biomedical sensors, wearable electronics, wireless communication modules, microcontroller platforms, and other low-power IoT technologies. The student will develop selection criteria based on power consumption, operating voltage requirements, functionality, and relevance to RF energy harvesting applications.

Following device selection, the student will assist in procuring hardware and developing standardized experimental test procedures. This will include designing and assembling test setups capable of measuring power consumption, startup energy requirements, current profiles, impedance characteristics, and operational behavior under different power conditions. The student will use laboratory instrumentation such as power supplies, oscilloscopes, multimeters, and data acquisition systems to collect and analyze performance data.

A major component of the project will involve evaluating device performance under realistic RF energy harvesting conditions. The student will investigate operation under intermittent, fluctuating, and constant power availability scenarios to identify operational thresholds, reliability limits, and energy requirements. Experimental results will be used to develop device models and create a searchable database that can be used by future researchers when designing RF energy harvesting systems.

The student will also document testing procedures, measurement protocols, and device characterization results to ensure reproducibility and future use within the research group. Additional responsibilities will include data analysis, technical reporting, and contributions to conference papers, technical reports, and scholarly publications arising from the project.

Skills required:
The ideal student will be enrolled in Electrical Engineering, Computer Engineering, Mechatronics Engineering, Physics, or a related discipline and have an interest in wireless technologies, electronics, and experimental research. Experience with electronic circuit testing, laboratory instrumentation, data analysis, and programming is desirable. Familiarity with microcontrollers, sensors, embedded systems, or RF concepts would be beneficial but is not required. The student should possess strong analytical and problem-solving abilities, attention to detail, and the ability to conduct systematic experimental investigations. Effective written and verbal communication skills and the ability to work independently and collaboratively are essential.

Research area: Wireless communications, signal processing, large intelligent surface, MIMO communications, detection and estimation, performance analysis.

Student roles:
Numerical simulation and presentation of results, mathematical calculation and analysis (if interested), report writing.

Skills required:
Advanced programming skills with MATLAB and basic knowledge of communications.

Research area: Our research lab studies physical human-robot interaction in the context of collaborative industrial robotics. Specifically, we specialize in the following fields: 1) Robotic manipulator dynamics modelling, which is important for identifying the full capabilities of a manipulator’s actuators. 2) High-performance motion optimization, which is vital for exploiting these capabilities. 3) High-performance computing for robotics control and optimization, which provides manipulators with the ability to react quickly to a dynamic environment. 4) Human-robot interaction modelling, and detection allow humans and robots to work together to achieve a task that neither would be able to do as efficiently alone.

Student roles:
The student will work in coordination with the project supervisor to:
• Conduct a literature review on lightweight flexible robotic arms, advanced composite materials, bio-inspired mechanical designs, and embedded sensing for compliant robots.
• Develop conceptual mechanical designs for flexible arm links and innovative joint mechanisms (e.g., variable stiffness, compliant joints) using CAD software.
• Perform preliminary material selection and analysis for arm components, considering factors like stiffness, weight, and suitability for embedding sensors.
• Design and prototype test fixtures or simple experimental setups to evaluate the mechanical properties (e.g., flexibility, stiffness profiles) of designed components or material samples.
• Assist in developing strategies for the co-design of mechanical structures with integrated proprioceptive sensors, considering sensor placement and robust integration.
• (If applicable) Conduct basic simulations (e.g., FEA) to analyze the deformation of flexible links under load or to predict the behavior of novel joint mechanisms.
• Document design iterations, experimental procedures, and results meticulously.
• Write a comprehensive project report summarizing the work undertaken, key findings, challenges faced, and potential directions for future research.
The following objectives will be considered extras to be completed if the above objectives are quickly met:
• Develop and fabricate a functional prototype of a key mechanical component or a section of the flexible arm.
• Explore basic control strategies that could leverage the designed mechanical intelligence for state estimation or safe interaction.
• Assist with other related research activities or experiments within the lab.

Skills required:
A strong foundation in mechanics, material science (especially composites and flexible materials), and mechanical design (CAD). Understanding of robot kinematics and dynamics. Knowledge of actuator types (especially lightweight/distributed systems) and their integration into mechanical systems. Familiarity with joint design and variable stiffness mechanisms would be a plus. Experience or interest in sensor integration, particularly proprioceptive sensors. Ability to understand and contribute to the modeling of flexible structures and how mechanical design can simplify control and state estimation. A proactive approach to tackling complex design challenges and exploring novel solutions.

Research area: Digital Protection of Electrical Grids; Small Modular Reactors (Electrical Aspects)

Student roles:
Work alongside a PhD student

Skills required:
Electrical Engineering (Power, Control, Digital), Software Coding

Research area: Mohamed Lamine Fayçal Bellaredj a obtenu le diplôme d'ingénieur en électronique et le magister en physique de l'Université des Sciences et Technologies d'Oran (USTO), Bir El Djir, Algérie, respectivement en 2005 et 2007, ainsi que le doctorat. diplôme en micro-ingénierie de l'Université de Franche-Comté, Besançon, France, en 2013. Ses intérêts de recherche incluent l'acoustofluidique, les ondes acoustiques de surface et les dispositifs acoustiques à base de métamatériaux, l'ingénierie passive embarquée pour l'électronique RF, numérique et de puissance, l'hybride flexible. électronique (FHE), micro-ingénierie/nano-ingénierie, modélisation, fabrication et caractérisation de systèmes MEMS/nanoélectromécaniques (NEMS), physique et technologie des dispositifs à semi-conducteurs et cellules solaires

Student roles:
Revue bibliographique
Conception et fabrication
Rédaction de rapports et de publications (encouragée)

Skills required:
Formation en ingénierie électrique, sciences des matériaux, physique etc.

Research area: I specialized in power electronics, machines, and drives (PEMD). My research interests include, but are not limited to, power electronic converters, energy storage systems, motor drives, and the reliability and diagnostics of PEMD systems.

Student roles:
The selected internee will collaborate with a PhD student in the following tasks:
- Generate and analyze fault signature datasets from simulations and experiments
- Perform signal processing and feature extraction
- Implement basic machine learning algorithms for fault classification
- Compare diagnostic performance under different operating conditions
- Prepare technical documentation and presentations

Skills required:
Nice to have the following skill sets:
- Fundamentals of power electronics and electrical circuits
- Basic programming skills in Python or MATLAB
- Interest in artificial intelligence and data analysis
- Knowledge of signal processing is beneficial
- Strong motivation for research and learning

Research area: Dr. Al Janaideh’s specialized research area focuses on adaptive optics, intelligent opto-mechatronic systems, and precision control technologies for advanced motion systems and optical applications. He is within the Fraunhofer Institute for Applied Optics and Precision Engineering, Germany, where his research investigates the development of adaptive optical systems capable of real-time wavefront correction and intelligent surface shaping. His work integrates deformable mirrors, MEMS-based optical devices, smart actuators, advanced sensing, system identification, and AI-enabled control algorithms to improve optical performance under dynamic conditions to support next-generation adaptive optics for astronomy, free-space quantum communication, and optics in lithography machines.

Student roles:
The undergraduate student will play an active role in the development and testing of advanced adaptive optics (AO) technologies for satellite-to-ground quantum communication systems. During the 12-week internship, the student will contribute to three main objectives of the project: improving wavefront sensor measurements using physics-informed machine learning, developing predictive control algorithms for atmospheric turbulence compensation, and modeling deformable mirror (DM) dynamics for enhanced control performance. A major component of the internship will be hands-on experimental work using state-of-the-art adaptive optics platforms. The student will gain practical experience with an AO platform from Thorlabs equipped with a piezoelectric deformable mirror and an AO platform from ALPAO featuring a magnetic deformable mirror, allowing them to compare different actuator technologies and control strategies. In addition, activities will include system calibration, wavefront measurement using a Shack-Hartmann wavefront sensor, mirror characterization, data acquisition, real-time control implementation, and performance evaluation under simulated turbulence conditions.

The student will also develop MATLAB and Python programs for data analysis, machine learning model development, system identification, and control algorithm testing. These tools will be used to process wavefront sensor data, train and validate predictive models, and evaluate closed-loop AO performance in terms of residual wavefront error and coupling efficiency. The student will assist in implementing basic real-time control loops and in comparing classical integrator-based control with data-driven predictive approaches. In addition, the student will support experimental validation by collecting and organizing datasets from both the Thorlabs piezoelectric DM system and the ALPAO magnetic DM system. They will help document system behavior, identify performance limitations, and relate observed results to theoretical models of atmospheric turbulence and actuator dynamics. Throughout the internship, the student will participate in weekly research meetings, present progress updates, and prepare a journal paper. The internship will provide direct exposure to advanced optical hardware and experimental research.

Skills required:
Undergraduate students in electrical engineering, mechatronics, physics or related fields are encouraged to apply. Students should have a background in programming, mathematics, system modeling, control systems and engineering problem-solving. Experience with MATLAB, Python, signal processing, control, and machine learning is required. The project will provide hands-on training in adaptive optics, artificial intelligence, data analysis, wavefront sensing, deformable mirror control, and experimental optical systems. Students should be motivated to learn new concepts and work in a multidisciplinary research environment involving both simulation and laboratory experiments. Strong analytical thinking, communication skills, and teamwork abilities are essential for success in this research internship.

Research area: printed electronics and sensors

Student roles:
The intern will be involved in the choice of the nature of the deposited thin films. The intern will be responsible for a short literature review on the methods on how to deposit such thin films to select both the tool used for deposition and which parameters to modify to optimize the optical, mechanical and electrical properties of the deposited thin films. The intern will be trained in how to measure such properties. Due to the relatively long deposition time the intern will be expected to be able to run tasks in parallel to optimize the properties of at least two thin films deposited with two different methods.
The intern will be supported by graduate students and two associate researchers. The intern will be provided with the opportunity and expected to work in a clean room environment.

Skills required:
Students should have knowledge of materials science, chemistry, electrical engineering, or a related discipline, with a particular interest in functional materials and device fabrication. Experience with laboratory techniques such as solution preparation, thin-film deposition, and electrical measurement is valuable. Analytical skills, attention to detail, and the ability to work collaboratively in a laboratory setting are essential. Effective communication and documentation skills are also important for sharing results and troubleshooting experimental challenges.

Research area: My area of research includes robotics, haptics, medical robotics, virtual fixtures, stability analysis, control systems, surgical robots, and smart surgical tools.

Student roles:
The student will design and develop the circuit board and test and evaluate it.

Skills required:
Electronic circuit design including amplifiers, FTDI, analog to digital converters, digital to analog converters, microprocessors, microcontrollers, programming of firmware.

Research area: My main research areas are: • Fuel cell and supercapacitors electric vehicles • Renewable energy (Solar, Wind, : conversion, storage, management, optimization and grid integration • Multiport and soft switching power electronic converters • DC and AC Drivers • Control and optimisation of power electronics systems (drives, power supplies, ...) • Implementation of control algorithms, energy management and optimization in VLSI and ULSI (ASCs, DSPs, FPGAs) technology • dedicated power supplies (high current / low voltage, pulsing) for plasma

Student roles:
The candidate will join a group of 4 researchers working on this project.

• The candidate must study and simulate some parts of the complete electronic system which is made up of a voltage inverter and DC-DC converters with several ports (multiport) which interfaces the sources to PEM electrolyzer.

• Explain in detail the generation of high-resolution phase shifts technic to control the power flow to the load.

• Integrat tools like Simscape to develop and implement control algorithms on a FPGA.

Skills required:
The candidate must have a good background in power electronics, automatic and knowledge of Matlab / Simulink environment and Simscape toolbox and Xilinx System Generator .

Research area: Development of Medical Devices incorporating Advanced Imaging Algorithms and the use of Machine Learning to improve the reconstruction of medical images, reduce radiation dose and diagnose disease using Positron Emission Tomography and Microwave Imaging.

Student roles:
Depending on the skill-set of the student, the student will be involved in the design, manufacture and testing of various facets of the portable system. This includes the development and refinement of the mechanical, electrical and computational components of the hardware, a graphical user interface designed for illiterate users, the microcomputer control system, and the collection of data from the detector array as a function of energy, position, and transmitter orientation. The student may be involved in collecting and analyzing the experimental and/or clinical data and the development and testing of a machine learning network to evaluate the measured data for the presence of breast abnormalities.

Skills required:
The student is required to be an independent learner with strong communication skills and a background in; Applied Physics, Electrical or Computer Engineering, or Computer Science. The successful student will have a good understanding of microwave electronics and electromagnetism and will be comfortable using and programming microprocessors. Experience with Machine Learning and Matlab/Python will be an advantage. The student will be expected to be creative and innovative, capable of working well in a diverse team and will have demonstrated undergraduate research experience that includes 3-D printing, electronics, programming, data collection and analysis, ideally in the medical field.

Research area: Printed electronics and sensors

Student roles:
Students involved in developing the Flexible batteries will be crucial in advancing the design, fabrication, and testing of cutting-edge flexible energy storage solutions. Their primary responsibilities will encompass reproducing a flexible zinc-manganese dioxide (Zn/MnO₂) battery that can maintain high performance under mechanical stress. Students will collaborate closely with a team of materials scientists and engineers, who are working on the flexible electronics.
Students are tasked with researching the basic principles of battery operation and familiarizing themselves with the materials and safety protocols involved. They then prepare the necessary inks and solutions, carefully measuring and mixing components to achieve the right consistency and properties for printing. This step requires attention to detail and an understanding of how each ingredient affects the overall performance of the battery.
During the fabrication phase, students use printing or coating techniques to apply each layer of the battery onto a flexible substrate. They must follow the correct order of assembly, ensure even application, and handle the materials with care to avoid contamination or defects. As the device takes shape, students are encouraged to document their process, noting any challenges or adjustments made along the way.
Once the battery is assembled, students move on to testing and characterization. They use laboratory equipment to measure key properties such as voltage, capacity, and flexibility, and analyze the data to evaluate the battery’s performance. If issues arise, students are expected to troubleshoot, propose solutions, and make improvements to their processes or materials.
Throughout the project, students develop teamwork and communication skills by dividing tasks, sharing results, and presenting their findings. They are also responsible for maintaining a safe and organized workspace, following all safety guidelines.

Skills required:
Students should have a background in chemistry, materials science, electrical and/or chemical engineering, or a related field, focusing on electrochemistry and nanotechnology. Experience with battery technology, particularly in design and fabrication, is valuable. Being open to working with flexible materials such as polymers and nanocomposites under the supervision of a material scientist, along with hands-on laboratory skills in material characterization and electrochemical testing, is valuable. Strong analytical and problem-solving abilities and effective communication and teamwork skills are crucial for successful project participation.

Research area: Dr. Mohammad Khondoker's areas of interest include developing smart additive manufacturing (AM) technologies, 3D printing of unconventional materials, designing polymer-based composite materials, chemical processing or treatments of functional materials, synthesis of nanomaterials, and rheological/mechanical characterizations. Dr. Khondoker has previously developed AM systems to print liquid metal-based stretchable electronics, parts made of intermixed extrudates of chemically immiscible polymers, devices consisting of extremely soft thermoplastic elastomers, etc.

Student roles:
1. Design the deposition head with a co-axial collimating nozzle.
2. Perform computational fluid dynamics analysis of the deposition head
3. Integrate the custom deposition head with a household ultrasonic humidifier
4. Characterize the deposition of the mist flow generated by the humidifier
5. Optimize and propose the printing parameters to achieve the finest possible tracks of deposited material

Skills required:
The ideal student candidate for this project should have experience with mechanical design and CAD modeling, material science and characterization, and polymer 3D printing. Experience with SEM, rheological analysis, and UV curable vitrimer epoxy would be an added advantage.

Research area: My research focuses primarily on high-voltage engineering, diagnostics, and the reliability of power equipment, particularly transformers. My work specifically addresses the aging of liquid–paper insulation systems, dissolved gas analysis (DGA), advanced insulating liquids (natural and synthetic esters), and the development of innovative monitoring and diagnostic approaches integrating artificial intelligence, advanced sensors, and digital twins for next-generation power networks.

Student roles:
The physical model to develop should allow to:
- Investigate the viscoelastic and viscoplastic relaxation behaviour of cellulose and aramid pressboard under combined mechanical and thermal stress in Mineral Oil (MO).
- Evaluate viscoplastic creep and the associated loss of clamping pressure.
- Continuously measure deformation and clamping force in real time.
- Track the evolution of pressboard moisture content throughout the experimental procedure.

Skills required:
electrical engineering, mechanical processing, data acquisition

Research area: Dr. Fang's research interests mainly focus on advanced drive systems toward transportation electrification, especially the advanced control of switched reluctance machines and permanent magnet synchronous machines. Dr. Fang was named on the World's Top 2% of Scientists and Engineers list by a Stanford University study. Dr. Fang also serves as an Associate Editor of IEEE Transactions on Transportation Electrification.

Student roles:
The student will mainly focus on digital current controller algorithm development.

Skills required:
The undergraduate applicant should currently be enrolled in the Engineering discipline and be proficient in English.

Research area: Mohamed Lamine Fayçal Bellaredj a obtenu le diplôme d'ingénieur en électronique et le magister en physique de l'Université des Sciences et Technologies d'Oran (USTO), Bir El Djir, Algérie, respectivement en 2005 et 2007, ainsi que le doctorat. diplôme en micro-ingénierie de l'Université de Franche-Comté, Besançon, France, en 2013. Ses intérêts de recherche incluent l'acoustofluidique, les ondes acoustiques de surface et les dispositifs acoustiques à base de métamatériaux, l'ingénierie passive embarquée pour l'électronique RF, numérique et de puissance, l'hybride flexible. électronique (FHE), micro-ingénierie/nano-ingénierie, modélisation, fabrication et caractérisation de systèmes MEMS/nanoélectromécaniques (NEMS), physique et technologie des dispositifs à semi-conducteurs et cellules solaires

Student roles:
Revue bibliographique
Conception et fabrication
Rédaction de rapports et de publications (encouragée)

Skills required:
Formation en ingénierie électrique, sciences des matériaux, physique etc.

Research area: Mohamed Lamine Fayçal Bellaredj a obtenu le diplôme d'ingénieur en électronique et le magister en physique de l'Université des Sciences et Technologies d'Oran (USTO), Bir El Djir, Algérie, respectivement en 2005 et 2007, ainsi que le doctorat. diplôme en micro-ingénierie de l'Université de Franche-Comté, Besançon, France, en 2013. Ses intérêts de recherche incluent l'acoustofluidique, les ondes acoustiques de surface et les dispositifs acoustiques à base de métamatériaux, l'ingénierie passive embarquée pour l'électronique RF, numérique et de puissance, l'hybride flexible. électronique (FHE), micro-ingénierie/nano-ingénierie, modélisation, fabrication et caractérisation de systèmes MEMS/nanoélectromécaniques (NEMS), physique et technologie des dispositifs à semi-conducteurs et cellules solaires

Student roles:
Revue bibliographique
Conception et fabrication
Rédaction de rapports et de publications (encouragée)

Skills required:
Formation en ingénierie électrique, sciences des matériaux, physique etc.

Research area: My research interests are dynamics, control, and motion planning of robotic and autonomous systems with focus on intelligent manufacturing and industrial applications. This includes, but is not limited to, unmanned aerial vehicles, spacecraft, space mechanisms, and robotic manipulators. My research work encompasses a broad spectrum, ranging from dynamics modeling for complex systems, robust controller design, trajectory optimization, vibrations, contact mechanics, mechanical design and stress analysis, energy-saving controllers and trajectories, and testing and validation.

Student roles:
The student will collaborate closely with a graduate student on dynamics modeling and controller design for robotic manufacturing tasks. Student's responsibilities include:
(1) Conducting literature review and identifying research gaps.
(2) Developing a dynamics model of the robotic system.
(3) Designing at least one controller for the manufacturing task; high-performing students may design two and compare performance.
(4) Proving controller stability mathematically in collaboration with a graduate student.
(5) Running simulations to evaluate controller performance.
(6) Experimentally validating controllers on industrial robots.
(7) Summarizing results in a report, with potential to co-author a publishable research paper.

The student will gain hands-on experience with modeling, control design, simulation, experimentation, and technical reporting. The student will learn to work collaboratively in an interdisciplinary and supportive research environment and develop skills essential for robotics research and industrial applications.

Skills required:
The student should meet at least three of the following:
(1) background in mechanical, electrical, mechatronics, robotics, control, manufacturing, or autonomous systems;
(2) strong mathematics foundation;
(3) experience with dynamics modeling and control design;
(4) programming skills in Python and/or MATLAB/Simulink (low level programming, e.g., C++, is an asset).

Hands-on robotics experience is a plus. Students must be team-oriented, value diversity, and be available full-time for the internship.

Research area: The main research area is Smart Electric Grids including the following research themes: 1- Power quality and data analytics. 2- Smart distribution system design, management and optimization. 3- Renewable energy and distributed generation integration. 4- Transportation electrification 5- Energy monitoring/management and smart metering. 6- Asset management and optimization. 7- Microgrid. 8- Artificial Intelligence and 9- Fault detection and classification.

Student roles:
The student is expected to work with Matlab, use datasets, apply machine learning to perform classification of motor faults.

Skills required:
Electric circuits/power and Machine learning programming in Matlab.

Research area: At the Nanoscale Optics Lab, we develop the next generation of technologies that will enable quantum leaps in computing, telecommunications, photovoltaics, sensing and display technologies. Group leader, Behrad Gholipour is an expert in chalcogenide semiconductors, optical fibres, material discovery and dielectric/plasmonic metamaterials/metasurfaces. In all these cases, he is interested in light-matter interaction with a focus on optoelectronic switching phenomena and novel nanofabrication techniques. He has pioneered ground-breaking technologies which are being pursued by many researchers/companies around the world. His work has resulted in global news coverage and >100 journal/conference publications including those in Science, Nature Photonics and Advanced Materials journals.

Student roles:
Aside from being involved in exploring various nanopatterning techniques. through this work, you will get a chance to work on finite difference time domain simulations of various nanopatterned films, the nanoscale growth of novel materials (using sputtering and evaporation) on various types of specialized substrates in a cleanroom environment as well as hands-on experience in various characterization techniques, in particular scanning electron microscopy, variable angle ellipsometry and microspectrophotometry.

Skills required:
Applicants from all relevant backgrounds in engineering are invited to apply. Applicants with a background in electronics, material science, physics, chemistry and an interest/previous experience in nanotechnology and photonics would be preferred.

Research area: - Wireless communication and networks - Resource allocation and optimization - Machine learning

Student roles:
- Literatur review of target detection approaches in wireless networks
- Literature review of data fusion approaches
- Literature review of quantum machine learning
- System modeling for target detection
- Collection of datasets relevant to the problem (RF signals + images)
- Testing of existing approaches for target detection using the datasets
- Development of a new framework for target detection using different techniques of data fusion that would integrate quantum machine learning
- Evaluation of benchmark methods and proposed approach in terms of target detection accuracy, precision, F1-score, etc.
- Preparation of a draft article

Skills required:
- Good knowledge of communication systems, in particular wireless communications
- Advanced skills in programming (Matlab or Python)
- Good knowledge of working with machine learning algorithms
- Very good mathematical background

Research area: - Data processing - Statistical signal processing - Probabilistic modelling

Student roles:
The student will contribute to developing and testing algorithms that separate individual player skill from collective team outcomes, using synthetic and real-world sport data. They can orient toward mathematical analysis or toward software implementation, based on their interests.

Skills required:
- Background: engineering (electrical/computer), mathematics or statistics
- Programming : usage of high-level programming languages or scripts (python)
- Autonomy : self-learning capacity

Research area: Mohamed Lamine Fayçal Bellaredj a obtenu le diplôme d'ingénieur en électronique et le magister en physique de l'Université des Sciences et Technologies d'Oran (USTO), Bir El Djir, Algérie, respectivement en 2005 et 2007, ainsi que le doctorat. diplôme en micro-ingénierie de l'Université de Franche-Comté, Besançon, France, en 2013. Ses intérêts de recherche incluent l'acoustofluidique, les ondes acoustiques de surface et les dispositifs acoustiques à base de métamatériaux, l'ingénierie passive embarquée pour l'électronique RF, numérique et de puissance, l'hybride flexible. électronique (FHE), micro-ingénierie/nano-ingénierie, modélisation, fabrication et caractérisation de systèmes MEMS/nanoélectromécaniques (NEMS), physique et technologie des dispositifs à semi-conducteurs et cellules solaires

Student roles:
Revue bibliographique
Conception et fabrication
Rédaction de rapports et de publications (encouragée)

Skills required:
Formation en ingénierie électrique, sciences des matériaux, physique etc.

Research area: Mon domaine de recherche est axé sur le développement des dispositifs quantiques et photoniques avancés et leur intégration dans des systèmes intelligents pour la surveillance en temps réel. En combinant les principes de la physique quantique, de l’ingénierie des matériaux, et de l’Internet des Objets (IoT), mes travaux visent à concevoir des dispositifs de détection ultra-sensibles, capables de fonctionner dans des environnements complexes, notamment dans les secteurs de l’électronique de pointe et de la cybersécurité matérielle.

Student roles:
L’étudiant(e) interviendra dans la préparation des layouts, l’adaptation des conceptions aux contraintes technologiques, le suivi des procédés de microfabrication et la caractérisation des circuits. Elle analysera les données expérimentales à l’aide d’outils Python, participera à l’amélioration des performances et contribuera à la documentation scientifique et technique du projet.

Skills required:
Le candidat idéal possède une formation en physique appliquée, génie électrique ou nanotechnologie, avec des connaissances en électroniques et/ou microélectroniques. Des compétences en programmation scientifique, modélisation et conception numérique ou analyse de données expérimentales sont souhaitées. Une expérience en conception des dispositifs quantiques-photoniques est un atout. Le candidat doit faire preuve de rigueur scientifique, de curiosité intellectuelle et être capable de travailler de manière autonome tout en collaborant au sein d’un environnement de recherche multidisciplinaire.

Research area: Microsystems, VLSI, Thermal dynamics, Thermal monitoring on microsystem, Thermal diffusion on biological tissues. Technology IP Porting.

Student roles:
- Familiarity with the basic principles of digital signal processing (DSP).
Choosing the best model for implementation,
- Implementation of a module in the Matlab-Simulink.
BEEcube plateforme design flow,
- Allow deepen the aspects related to the hardware and Layout porting for IC
-Schematic modeling & simulation
- Post Layout simulation

Skills required:
CMOS 65nm and 28 nmProcess
Knowledge of programming languages
VB.Net, ASP.NET, HTML/CSS, SQL, Java, C++, C, C#, XML, QT, GWT, Programing Embedded
Systems, Shell, Object-Oriented Design.
Familiar with: Pascal, PL/SQL, UML, VBScript, Prolog, VHDL.
- Pretty solid knowledge of digital signal processing and be familiar with Matlab, VHDL, Verilog

Research area: Digital Operation, Protection of Electrical Grids; Small Modular Reactors (Electrical Aspects)

Student roles:
Work alongwith a PhD student.

Skills required:
Electrical Engineering (Power & Control), Software Coding

Research area: My research mainly focuses on critical areas related to power systems. The three main areas of my research are: i) modeling, ii) protection and iii) control of HVDC systems and VSC-interfaced renewable energy resources. The overall objective of my research is to investigate and overcome the challenges associated with the realization of mixed AC-DC power systems and renewable energyresources.

Student roles:
The student will be involved in developing the model of various protection and control system components for an HVDC grid in a power system simulation software. The student should analyze the simulation results and compare the performance of various relays and controllers. The students should provide a report of their project results of the internship. Throughout this research internship, several undergraduate students will receive training in the fields of HVDC operation, protection and control, which have strategic importance to the power industry. The students may get to work with a real-time digital simulator if the time allows.

Skills required:
The students need to have a basic knowledge in power systems and power electronics.

Research area: Our lab is very interdisciplinary - we are located in physics and some days we're a physics lab, other times we are a chemistry lab, and other times we work on engineering devices. We are really interested in optics and color, and we have an active lab with numerous optical equipment including various lasers, spectrometers, cryostats, and a lot of measuring equipment. I also teach undergraduate optics, which is one of the most important disciplines that touches almost all fields of physics and many aspects of chemistry and engineering.

Student roles:
The student will be trained in the experimental methods and will conduct experiments. They will eventually be a leader on their own project, ideally. They'll be a full member of a research team and will interact daily with myself and our grad students, and likely collaborating researchers as well.

The intern will be involved in several or all aspects of the project, and to give a few specifics, we should mention the items below:
- Sample preparation (polymers, thin films, devices).
- Nanofabrication
- Optical characterization including fluorescence spectroscopy and microscopy
- Handling of class-IV lasers (safety training to be performed here)
- Data analysis and processing in Mathematica and/or Python
- Working as a team member with other students and supervisor
- Having ideas and having fun as part of an interdisciplinary research group
- Work towards getting a scientific publication in a peer reviewed journal

Skills required:
The project is quite interdisciplinary, involving aspects of optical physics, electrical engineering, and organic chemistry. That's why we would be happy with students with backgrounds in engineering, physics, or chemistry. We also want people who are handy and excited about laboratory work and developing those skills in addition to theory. Some ability with Python or Mathematica is especially nice, but not strictly required, as much of this can be learned in the lab.

Research area: My main research area centers on next‑generation wireless communication systems, with a strong focus on integrated terrestrial and non‑terrestrial networks, unmanned aerial vehicle (UAV) communications, high-altitude platforms stations (HAPS), resource allocation, edge computing, and machine learning for communication networks.

Student roles:
- Contribute to the modeling and analysis of Integrated Sensing and Communication (ISAC) systems operating within non‑terrestrial networks such as UAVs, satellites, or high‑altitude platforms.
- Develop and implement simulation frameworks, typically in MATLAB or Python, to evaluate communication performance, sensing accuracy, and system trade‑offs.
- Assist in designing or refining algorithms for joint communication and target localization, including signal processing or optimization‑based methods.
- Review and synthesize scientific literature on ISAC, NTN architectures, and related wireless technologies to support the project’s theoretical foundation.
- Analyze simulation results, interpret system behavior, and help prepare technical reports, figures, or research summaries.
Collaborate with the supervising professor and research team, contributing ideas and participating in discussions on system design and performance improvements.

Skills required:
- Strong foundation in wireless communications (channel models, propagation, communication system design)
- Knowledge of signal processing (estimation, detection, localization techniques)
- Familiarity with non‑terrestrial networks, UAV communications, or satellite systems
- Solid understanding of mathematical modeling and algorithm development
- Proficiency in MATLAB and/or Python for simulation and analysis
- Experience with scientific computing tools (e.g., NumPy, SciPy, Simulink)
- Background in optimization or machine learning is an asset
- Ability to work independently, think analytically, and engage with emerging wireless technologies

Research area: Interdisciplinary areas of applied electromagnetics and wireless communications, with a particular focus on the development of high-performance computational models/algorithms for emerging wireless technologies in 5G/6G/THz wireless communications, intelligent transportation (air, ground, underground), underwater communications, industrial Internet of Things, as well as biomedical sensing and healthcare applications. Keywords: Applied Electromagnetics, 5G/6G Wireless, Integrated Sensing & Communication, Localization, Antennas & RF/Microwave Design, Machine Learning & Parametric Modeling, Stochastic Uncertainty Quantification, Internet of Things & Intelligent Systems.

Student roles:
(1) Assisting in conducting literature reviews to gather relevant research papers, articles, and other academic resources to support the research project.
(2) Collaborating with the research team to exchange ideas, share knowledge, and contribute to the overall research goals, including methodology & model development, results analysis, etc.
(3) Participating in group meetings, and effectively communicating project progress and results.
(4) Keeping records of research procedures, observations, and findings. Writing reports, summaries, and contributing to scientific papers writing or presentations.

Skills required:
The project suits students with interests and background in mathematics, electromagnetics or communication theory, and programming.

Research area: My research area is Control Engineering, including both control theory and its applications to engineering problems. The application areas of interest are floating offshore wind turbines and wind farms, solar thermal systems, automotive engines and aftertreatment systems, and additive manufacturing processes. Theoretically, physics-based and data-driven modeling, robust and optimal model-based controller design and reinforcement learning control are the key research interests.

Student roles:
The student's roles are to collect input and output data in simulations of floating offshore wind farms, to build a mathematical model based on the data, to design controllers based on the model, and to validate the controllers in simulations. The student will have regular meetings with the supervisor and graduate students, where they report their progress and short and long term plans. At the end of the internship period, the student will write a report which may eventually become a conference or journal paper.

Skills required:
The student should have a basic control background. It is also preferable (but not mandatory) that the student knows modern control (i.e. state space control) techniques. The student should be familiar with Matlab/Simulink. Student's strong interest in sustainable energy systems in general and wind turbines specifically will be an asset. It is ideal (but not mandatory) that the student knows some machine learning techniques, such as neural network and reinforcement learning. The student should have strong communication skill in both speaking and writing, and strong interpersonal skill for team work.

Research area: Our research lab studies physical human-robot interaction in the context of collaborative industrial robotics. Specifically, we specialize in the following fields: 1) Robotic manipulator dynamics modelling, which is important for identifying the full capabilities of a manipulator’s actuators. 2) High-performance motion optimization, which is vital for exploiting these capabilities. 3) High-performance computing for robotics control and optimization, which provides manipulators with the ability to react quickly to a dynamic environment. 4) Human-robot interaction modelling, and detection allow humans and robots to work together to achieve a task that neither would be able to do as efficiently alone.

Student roles:
The student will work in coordination with the project supervisor to:
• Conduct a literature review on lightweight flexible robotic arms, advanced composite materials, bio-inspired mechanical designs, and embedded sensing for compliant robots.
• Develop conceptual mechanical designs for flexible arm links and innovative joint mechanisms (e.g., variable stiffness, compliant joints) using CAD software.
• Perform preliminary material selection and analysis for arm components, considering factors like stiffness, weight, and suitability for embedding sensors.
• Design and prototype test fixtures or simple experimental setups to evaluate the mechanical properties (e.g., flexibility, stiffness profiles) of designed components or material samples.
• Assist in developing strategies for the co-design of mechanical structures with integrated proprioceptive sensors, considering sensor placement and robust integration.
• (If applicable) Conduct basic simulations (e.g., FEA) to analyze the deformation of flexible links under load or to predict the behavior of novel joint mechanisms.
• Document design iterations, experimental procedures, and results meticulously.
• Write a comprehensive project report summarizing the work undertaken, key findings, challenges faced, and potential directions for future research.
The following objectives will be considered extras to be completed if the above objectives are quickly met:
• Develop and fabricate a functional prototype of a key mechanical component or a section of the flexible arm.
• Explore basic control strategies that could leverage the designed mechanical intelligence for state estimation or safe interaction.
• Assist with other related research activities or experiments within the lab.

Skills required:
A strong foundation in robot kinematics and dynamics, with emphasis on redundant and floating-base systems. Understanding of mobile platforms and their integration with serial manipulators. Knowledge of trajectory optimization and optimization-based control, including constraint formulation (kinematic limits, dynamic stability, collision avoidance). Familiarity with whole-body control and real-time solver implementation would be a plus. Experience or interest in state estimation and sensor fusion, particularly for localization and end-effector accuracy on a moving base. Ability to understand and contribute to the modeling of coupled base–arm dynamics and how control and estimation can be co-designed. Proficiency in C++ for real-time robotics.

Research area: My research work focuses on improving the security of computer systems in software, hardware, and firmware-levels. I am also interested in understanding security-related topics in machine learning (both security of ML and applications of ML to security). My work involves software design and deep learning, and I am particularly interested in the application of LLMs to software and hardware engineering, with a focus on understanding potential threats that may emerge from these new approaches.

Student roles:
Students will be expected to perform a mix of literature-based research and hands-on experimental implementation. Students will read and summarize the literature on this topic, curate and evaluate datasets that can be used in the research, and prototype frameworks for performing experiments on some element of the generative AI/security intersection. Students will be expected to work independently as well as participate in the research group through meetings, presentations, informal discussions, and possible hands-on collaboration during the project. Students should take the initiative, be creative, and be flexible. The student will be expected to write reports and meet regularly with the supervisor.

Skills required:
Successful students will have a strong background in either software design (e.g., object-oriented, scripting, or web-related development), or in digital hardware design (e.g., Verilog or SystemVerilog), including tools/techniques for design verification. Skills in a scripting language (especially Python) and using APIs are important. Hands-on experience in machine learning, such as using the HuggingFace platform and machine learning frameworks (like PyTorch, TensorFlow, scikit-learn), will be an asset. Cybersecurity experience is not required (but a motivation to learn more about the topic will be crucial!). Experience with, or a strong interest in learning, the process of doing research is required.

Research area: Dr. Fang's research interests mainly focus on advanced drive systems toward transportation electrification, especially the advanced control of switched reluctance machines and permanent magnet synchronous machines. Dr. Fang was named on the World's Top 2% of Scientists and Engineers list by a Stanford University study. Dr. Fang also serves as an Associate Editor of IEEE Transactions on Transportation Electrification.

Student roles:
The student will mainly focus on sensorless control algorithm development.

Skills required:
The undergraduate applicant should currently be enrolled in the Engineering discipline and be proficient in English.

Research area: My research interests are dynamics, control, and motion planning of robotic and autonomous systems with focus on intelligent manufacturing and industrial applications. This includes, but is not limited to, unmanned aerial vehicles, spacecraft, space mechanisms, and robotic manipulators. My research work encompasses a broad spectrum, ranging from dynamics modeling for complex systems, robust controller design, trajectory optimization, machine learning and AI applications, vibrations, contact mechanics, mechanical design and stress analysis, energy-saving controllers and trajectories, and testing and validation.

Student roles:
The student will collaborate closely with a graduate student on dynamics modeling and controller design for robotic manufacturing tasks. Student's responsibilities include:
1) Conducting literature review and identifying research gaps (Student 1 and Student 2).
2) Developing a machine learning algorithm to identify different objects in a cluttered environment based on color, shape, and or size (Student 1).
3) Developing a strategy to localize this object in the workspace (Student 1).
4) Developing a manipulation plan to pick this object from its current location and place it in a certain spot based on their characteristics, i.e., sorting, (Student 2).
5) Developing a obstacle avoidance technique to ensure that the objects will be placed safely without any collisions (Student 2).
6) Running simulations to evaluate these algorithms, strategies, and techniques (Student 1 and Student 2).
7) Experimentally validating these algorithms, strategies, and techniques on industrial robots (Student 1 and Student 2).
8) Summarizing results in a report, with potential to co-author a publishable research paper (Student 1 and Student 2).

The students will gain hands-on experience with machine learning, manufacturing systems, simulation, experimentation, and technical reporting. The students will learn to work collaboratively in an interdisciplinary and supportive research environment and develop skills essential for robotics research and industrial applications.

Skills required:
The students should meet at least three of the following:
(1) background in mechanical, electrical, mechatronics, robotics, control, manufacturing, or autonomous systems;
(2) background in machine learning, reinforcement learning, and/or AI.
(3) strong mathematics foundation;
(4) programming skills in Python and/or MATLAB/Simulink (low level programming, e.g., C++, is an asset).

Hands-on robotics experience is a plus. Students must be team-oriented, value diversity, and be available full-time for the internship.

Research area: My research focuses on antenna and RF front-end design for wireless communication, energy harvesting, and sensing applications. I am developing sustainable, reconfigurable systems that are enabling low-power, multifunctional operation for wearable and IoT applications. This includes rectennas that harvest ambient RF energy to reduce battery dependence and environmental impact, and integrated sensing and communication platforms for applications such as smart agriculture and wireless monitoring. My work addresses key challenges such as mechanical adaptability, interconnection reliability, and performance in dynamic environments, contributing to the advancement of efficient, resilient, and environmentally responsible wireless technologies

Student roles:
The student will take on a central role in advancing the research objectives of the project, which focuses on the development of mechanically reconfigurable antennas for wearable applications. These antennas must maintain stable performance despite the mechanical deformation typical of smart wearables, such as bending, stretching, or twisting during everyday use.
The student will begin by identifying and characterizing suitable flexible dielectric materials through literature review and empirical testing. This includes evaluating material properties such as permittivity, loss tangent, and mechanical stretchability under various conditions relevant to body-worn applications.
A key component of the role involves full-wave electromagnetic simulation and modeling using tools such as HFSS, CST Microwave Studio and Keysight ADS. The student will design and optimize antenna geometries integrated with mechanical tuning features such as adjustable clasps, fastener rings, and rotatable bezels, or reconfigurable magnetic connectors. These elements will be simulated to understand their impact on resonance frequency, bandwidth, and radiation patterns during deformation.
The student will also participate in the prototyping and fabrication of antenna designs using flexible substrates, and embedded tuners. This will be followed by experimental validation of performance using RF test equipment such as vector network analyzers, signal generators, and anechoic chambers at the Radiated Systems Research Lab (RSRL). Emphasis will be placed on verifying reconfigurability and reliability under mechanical actuation.
Throughout the project, the student will maintain detailed documentation, contribute to drafting technical reports and peer-reviewed publications, and present findings in group meetings and seminars. This hands-on experience will equip the student with critical skills in wearable antenna engineering, mechanical integration, and RF characterization, while fostering independent research capabilities, technical communication, and professional development in a highly interdisciplinary environment.

Skills required:
The ideal student should have a background in Electrical or Electronics Engineering with coursework or project experience in antenna design and RF systems. Proficiency in electromagnetic simulation tools such as CST or HFSS, is essential. Knowledge of flexible materials, wearable electronics, and basic mechanical deformation principles is highly desirable. Experience with prototyping techniques such as PCB fabrication is an asset. Experience with MATLAB or Python for data analysis would be beneficial. Strong skills in problem-solving, communication, time management, and documentation are valued and will support success in this role.

Research area: My expertise lies in applied electromagnetics, RF and microwave engineering, and electromagnetic sensing technologies. My research spans microwave circuits, antennas, advanced material characterization, and sensing systems, with applications in telecommunications, aerospace, and smart infrastructure. I develop innovative measurement and modeling techniques that integrate electromagnetics, multiphysics analysis, and data-driven methods to improve the performance, reliability, and functionality of next-generation engineered systems.

Student roles:
Based on the student's interests and skills, the following tasks are proposed:
1) Perusal of scientific and technical documentation for a proper understanding of the underlying principles of this technology.
2) Analysis of the scientific and technical documentation for research gap finding and proposal of potential solutions.
3) Design and tuning of microwave sensors using lumped-element and full-wave electromagnetic simulations (theoretical modelling, full-wave design, tuning of frequencies of operation, analysis of sensing metrics, sensitivities, selection of substrates, size adjustments, etc).
4) Implementation of the proposed design and experimental testing in controlled laboratory conditions. Validation of simulation results and retrofitting.
5) Design of portable devices integrating the microwave sensors, a microcontroller, and a display unit showing results instantaneously. Implementation of the final plug-and-play measurement system prototype.
6) Involvement in the experimental characterization campaign of new materials and analysis of the obtained results.
7) Writing of technical reports and scientific communications according to the progress and the results.
8) Proposal of future actions and potential improvements of the developed technology.

Skills required:
The ideal candidate should have a basic understanding of electromagnetism and electronics. PCB design skills, as well as Matlab/Phyton programming and prototyping skills, are required.
Previous experience in the use of laboratory equipment such as Network Analyzers, Signal generators, Oscilloscopes, and Spectrum Analyzers is desired.
Knowledge and experience with simulation tools such as ADS, HFSS, or CST are an asset.
The successful candidate must be able to present their work in English to the international team on a bi-weekly basis. The knowledge of French will be an asset.

Research area: My research specializes in advancing the design and autonomous capabilities of small spacecraft through a systems-level approach that integrates reliable power systems and onboard machine learning. I focus on developing and applying rigorous design methodologies to ensure scalability, efficiency, and resilience across all subsystems. This includes model-based design, hardware-in-the-loop testing, and modular components that support rapid prototyping and deployment. By addressing both hardware and software challenges, my work aims to enable next-generation small satellites capable of autonomous operation to support the New Space.

Student roles:
The student will contribute to the design and prototyping of a modular Electrical Power System (EPS) for small satellites, focusing on the integration of energy storage technologies such as lithium-based batteries and supercapacitors.
Initial tasks will include a literature review of EPS architectures and storage technologies to inform design decisions. The student will assist in modeling and simulating system configurations, analyzing performance trade-offs between DET, MPPT, and decentralized approaches.
The role involves hands-on circuit design, prototyping, and testing, as well as validating system performance through lab measurements and hardware-in-the-loop setups. The student will also support the development of control strategies for smart power management and contribute to documentation and reporting of results.
This position offers practical experience in satellite power systems and the opportunity to contribute to the development of adaptable, energy-efficient EPS solutions.

Skills required:
Students should be familiar with key concepts in power electronics, such as voltage regulation, DC-DC conversion, battery management, and energy harvesting. Prior experience with energy storage technologies, such as lithium-based batteries or supercapacitors—is highly desirable, along with an understanding of their operational characteristics, safety considerations, and integration challenges.
Proficiency in using electronic design tools (e.g., Altium Designer, KiCAD, or similar PCB layout software) and circuit simulation tools (e.g., LTspice, MATLAB/Simulink) is important. Experience with prototyping and testing power electronics circuits, working with development boards, or using lab instrumentation (oscilloscopes, power supplies, multimeters) will be a strong asset.

Research area: Resilient Positioning, Navigation and Surveillance for autonomous aerial and ground vehicles, with a focus on Signals of Opportunity (SoOP), low Earth orbit satellite signals, cellular networks, software-defined radio, sensor fusion, and robust PNT systems for GNSS-challenged environments.

Student roles:
The student will contribute to the development and validation of resilient navigation and surveillance methods based on Signals of Opportunity for autonomous aerial and ground vehicles. The main role will be to support the acquisition, processing, and analysis of alternative radio signals that can be used when GNSS is degraded or unavailable.

The student may participate in the implementation of signal processing algorithms, the configuration of software-defined radio platforms, the analysis of LEO satellite and cellular signals, and the evaluation of positioning or surveillance performance. The work may also include simulation, experimental data collection, laboratory testing, and comparison of different signal fusion strategies.

Depending on the student’s background, the role may involve programming in Python, MATLAB, or C/C++, working with real or simulated datasets, preparing technical documentation, and contributing to research demonstrations. The student will work under the supervision of researchers at the LASSENA laboratory and may interact with industrial or academic partners involved in the project.

The expected contribution is both practical and analytical: the student will help transform Signals of Opportunity into usable navigation and surveillance information for future resilient autonomous systems.

Skills required:
he ideal candidate should have a background in electrical engineering, computer engineering, aerospace engineering, telecommunications, software engineering, or a related field. Knowledge of signal processing, wireless communications, GNSS, software-defined radio, embedded systems, or navigation systems would be an asset.

Experience with Python, MATLAB, C/C++, software-defined radio platforms, data analysis, simulation tools, or machine learning methods is desirable. The student should be motivated, autonomous, rigorous, and interested in applied research involving real signals, laboratory experiments, and autonomous vehicle applications.

Good analytical skills, technical documentation abilities, and the capacity to work in a multidisciplinary research environment are strongly encouraged.

Research area: Interdisciplinary areas of applied electromagnetics and wireless communications, with a particular focus on the development of high-performance computational models/algorithms for emerging wireless technologies in 5G/6G/THz wireless communications, intelligent transportation (air, ground, underground), underwater communications, industrial Internet of Things, as well as biomedical sensing and healthcare applications. Keywords: Applied Electromagnetics, 5G/6G Wireless, Integrated Sensing & Communication, Localization, Antennas & RF/Microwave Design, Machine Learning & Parametric Modeling, Stochastic Uncertainty Quantification, Internet of Things & Intelligent Systems.

Student roles:
(1) Assisting in conducting literature reviews to gather relevant research papers, articles, and other academic resources to support the research project.
(2) Collaborating with the research team to exchange ideas, share knowledge, and contribute to the overall research goals, including methodology & model development, results analysis, etc.
(3) Participating in group meetings, and effectively communicating project progress and results.
(4) Keeping records of research procedures, observations, and findings. Writing reports, summaries, and contributing to scientific papers writing or presentations.

Skills required:
The project suits students with interests and background in mathematics, electromagnetics or communication theory, and programming.

Research area: Our research advances neuromorphic computing and its applications in edge AI and digital health technologies. We develop custom brain-inspired computational models alongside ultra-low-power neuromorphic hardware architectures. By tightly coupling these hardware-software systems, our goal is to enable real-time, on-device biosignal processing directly at the edge.

Student roles:
During this 12-week internship, the student will bridge software simulation with edge hardware deployment, taking ownership of the implementation and optimization of our neuromorphic ECG classification models on physical microcontrollers/FPGAs.
Key Responsibilities:
- Model Translation & Optimization: Adapt pre-trained brain-inspired or spiking neural network (SNN) models from Python environments into highly optimized, deployment-ready C/C++ code for MCUs or HDL code for FPGAs..
- Bare-Metal Firmware Development: Write structured, low-overhead bare-metal firmware to execute the algorithmic pipelines directly on low-power microcontrollers (MCUs) without relying on thick operating system layers.
- Sensor Interfacing & Data Ingestion: Develop driver software to handle real-time data ingestion of 1D ECG time-series signals via standard serial protocols (e.g., SPI or I2C), ensuring the microchip can process data streams efficiently.
- On-Chip Benchmarking: Deploy the bare-metal code onto target hardware dev boards and benchmark on-chip performance metrics, specifically analyzing execution latency, classification accuracy, memory footprint, and power consumption.
- Hardware Troubleshooting & Documentation: Work alongside laboratory mentors to debug embedded code using standard hardware debugging interfaces and compile comprehensive documentation, including clean GitHub repositories and a final technical report.

Through this hands-on role, the student will gain critical, real-world experience in embedded systems, edge AI, and hardware-software co-design within an interdisciplinary engineering environment.

Skills required:
Candidates should be upper-year undergraduate students in Computer Science, Computer Engineering, Biomedical Engineering, Electrical Engineering or a related discipline. Required skills include
- Strong proficiency in Python.
- Strong proficiency in Bare-Metal programming (C/C++) of low-power microcontrollers or HDL coding (SystemVerilog) for FPGAs.
- A solid understanding of digital signal processing (DSP) techniques, particularly for 1D time-series data or biological signals, is essential.
- Prior exposure to neuromorphic computing concepts, spiking neural networks (SNNs), or event-driven programming is highly desirable.

Research area: Digital Protection of Electric Grids; Small Modular Reactors (Electrical Aspects)

Student roles:
Work alongside a PhD student

Skills required:
Electrical Engineering (Power, Digital Communications); Software Coding

Research area: IoT security

Student roles:
- Develop a TinyML-based on-device framework for detecting and classifying freeze and replay attacks using multivariate air quality sensor data.
- Evaluate the impact of window-based data representations (L64) on detection accuracy and computational efficiency.
- Design lightweight machine learning models suitable for deployment on microcontroller-based IoT platforms.
- Assess the trade-offs between accuracy, latency, memory usage, and energy consumption using TinyML optimization techniques.

Skills required:
- Machine learning: feature extraction, classification, Lightweight neural networks and classical classifiers.
- IoT security: knowledge of attack types and IoT protocols.
- Python programming: with libraries like PyTorch, TensorFlow, scikit-learn.

Research area: My research mainly focuses on critical areas related to power systems. The three main areas of my research are: i) modelling, ii) protection and iii) control of HVDC systems, VSC-interfaced renewable energy resources and electric vehicles. The overall objective of my research is to investigate and overcome the challenges associated with the realization of modern power systems with integrated renewable energy sources and electric vehicles.

Student roles:
The student will be involved in developing the model of electric vehicles, including their chargers, in a power system simulation software. The student should analyze the simulation results and compare the performance of various chargers. The students should provide a report of their project results from the internship. Throughout this research internship, several undergraduate students will receive training in the fields of electric vehicle operation and control, which have strategic importance to the power industry.

Skills required:
The students need to have a basic knowledge in power systems and power electronics.

Research area: At the Nanoscale Optics Lab, we develop the next generation of technologies that will enable quantum leaps in computing, telecommunications, photovoltaics, sensing and display technologies. Group leader, Behrad Gholipour is an expert in chalcogenide semiconductors, optical fibres, material discovery and dielectric/plasmonic metamaterials/metasurfaces. In all these cases, he is interested in light-matter interaction with a focus on optoelectronic switching phenomena and novel nanofabrication techniques. He has pioneered ground-breaking technologies which are being pursued by many researchers/companies around the world. His work has resulted in global news coverage and >100 journal/conference publications including those in Science, Nature Photonics and Advanced Materials journals.

Student roles:
Through this work, you will get a chance to work on finite difference time domain simulations of various metamaterial architectures integrated with optical fibres, the nanoscale growth of novel materials (using sputtering and evaporation) on various types of optical fibres in a cleanroom environment as well as various nanoscale patterning tools (e.g focused ion beam milling and electron beam and photolithography). This will be backed up with hands-on experience in various characterization techniques, in particular scanning electron microscopy, variable angle ellipsometry and microspectrophotometry.

Skills required:
Applicants from all relevant backgrounds in engineering are invited to apply. Applicants with a background in electronics, material science, physics, chemistry and an interest/previous experience in telecommunication networks, handling and processing optical fibres, nanotechnology and photonics would be preferred.

Research area: • Resource and Mobility management in future wireless networks (5G/6G networks, O-RAN). • Cybersecurity in 5G/6G/O-RAN networks. • AI and Quantum AI for wireless networks. • Green networking and Green Cloud. • Computation Offloading in Mobile Edge Computing (MEC). • Smart cities and Software defined wireless networks. • Network Digital Twin.

Student roles:
1) Revue de la littérature :
• Étudier la littérature existante sur les différents functional splits dans les réseaux 5G, ainsi que la consommation énergétique dans les réseaux 5G. Trois articles ont été identifiés pour les étudiants.

2) Simulations et tests :
• Émuler le fonctionnement d'un réseau 5G en utilisant les émulateurs srsRAN, Open5GS, et des UE virtuels.
• Etendre la plateforme émulée en développant un algorithme de gestion de mobilité (Handover) d'un UE virtuel qui se déplace entre 2 cellules (i.e., 2 gNBs) gérées par un même DU (ditributed unit) dans un premier temps, puis par deux DUs différents.
• Implémenter l'algorithme développé sous forme de xAPP dans un controleur SDN.
• Interconnecter la plateforme émulée avec une plateforme de test 5G réelle à base d'OAI (OpenAirInterface) composée par 3 cartes USRP X310, et des UE réels (2 smartphones).
• Tester l'algorithme développé dans la plateforme hybride déployée dans l'étape précédente en utilisant les UEs réels connectés sur 2 gNBs différents.
• Exploiter les données de mobilité fourni par l'opérateur de télécommunication et appliquer un algorithme de Machine Learning (ML) pour prédire de manière optimisée la gestion de la mobilité dans le réseau.
• Tester l'algorithme ML développé dans la plateforme hybride 5G mentionnée ci-dessus.

Résultats attendus:
• Un cadre complet pour décider de l'optimisation de la gestion de mobilité dans un réseau SDN/5G en utilisant le Machine Learning.
• Documentation détaillée et analyse des performances du framework.
• Recommandations pour des améliorations futures et domaines potentiels de recherche ultérieure.

Skills required:
− Connaissance de l’architecture des réseaux 5G/6G
− Connaissance des outils de virtualisation et de conteneurisation : docker, Docker SWARM, Kubernetes
− Connaissance des contrôleurs SDN.
− Une connaissance du fonctionnement de l'émulateur OpenAirInterface est souhaitée : https://gitlab.eurecom.fr/oai/openairinterface5g
− Une connaissance du fonctionnement de l'émulateur srsRAN est souhaitée : https://github.com/srsran/srsran_project
− Connaissance du langage de programmation : Python, Java ou C++
− Connaissance des systèmes Linux

Research area: Investigator’s research area is focused on “Computer-Aided Design Tools and Methodologies for Analysis of High-Frequency Circuits, Systems and Mixed-Domain Applications”. The future trend towards higher operating speeds, sharper excitations and more complex designs demands essential changes in the VLSI design/verification methodologies and the associated computer-aided design (CAD) tools. With the increasing signal-speed and decreasing feature sizes, interconnect effects become the dominant factors limiting overall performance of microelectronic systems. Also modern designs are increasingly warranting seamless integration of heterogeneous modules such as MEMS, RF, electromagnetic and optoelectronic blocks etc. along with digital as well as analog blocks. Conventional methods and tools

Student roles:
1. Familiarize with the concept of design automation of large circuits with emphasis on modeling and simulation
2. Thorough literature survey of the background material
3. Participate and contribute to the development of novel CAD techniques focused on one or several of the following areas: signal integrity, power integrity, mixed-signal analysis methods, parallel computing techniques for design automation etc.
4. Develop/Implement efficient schemes for the proposed methods
5. Validate the developed concepts and prototypes via practical and industrial circuit examples.
6. Prepare and submit/present related innovations in IEEE transactions/conferences and prepare the report

Skills required:
-Sound mathematical and Analytical Ability
-Proficiency in programming (C or C++ or Matlab)
-Knowledge of circuit theory and electronic devices

Research area: My research mainly focuses on critical areas related to power systems. The three main areas of my research are: i) modeling, ii) protection and iii) control of HVDC systems and VSC-interfaced renewable energy resources. The overall objective of my research is to investigate and overcome the challenges associated with the realization of mixed AC-DC power systems and renewable energyresources.

Student roles:
The student will be involved in developing an algorithm to use PMU data to detect faults in a small power system test case. The student will build the model of the test system first and then will generate sample PMU data. Then, the student will be in charge of selecting the best method to analyze the PMU data for fault detection.

Skills required:
The students need to have a basic knowledge in power systems and power electronics.

Research area: Printed electronics and sensors

Student roles:
Students will play a central role in advancing the development of piezoelectric and triboelectric materials for energy harvesting and sensing applications. Their responsibilities begin with a literature review to understand the fundamental principles of piezoelectricity and triboelectricity, as well as the latest advances in material design and device integration. Students will then participate in the selection of suitable materials, such as polymers, ceramics, or composites, and will learn to process these into thin films or structured layers using techniques like spin-coating, drop-casting, or printing.
During fabrication, students will assemble prototype devices by layering materials onto flexible or rigid substrates, ensuring

Collaboration and communication are integral to the project. Students will work in teams, dividing tasks such as material preparation, device assembly, and data analysis. They will present their findings in group meetings, contribute to discussions on improving device performance, and maintain a safe, organized workspace. By the end of the project, students will have developed valuable skills in functional material development, device engineering, and scientific problem-solving preparing them for careers in advanced materials, electronics, and sustainable technology sectors.

Skills required:
Students should have knowledge of materials science, chemistry, electrical engineering, or a related discipline, with a particular interest in functional materials and device fabrication. Experience with laboratory techniques such as solution preparation, thin-film deposition, and electrical measurement is valuable. Familiarity with concepts in solid-state physics, nanotechnology, or polymer science will enhance understanding of the underlying mechanisms. Analytical skills, attention to detail, and the ability to work collaboratively in a laboratory setting are essential. Effective communication and documentation skills are also important for sharing results and troubleshooting experimental challenges.

Research area: Electric vehicles (EVs) will soon be a fact in our daily life due to new government regulations like the carbon tax. Efficient converters are eminent for a more efficient vehicle; new semiconductor-based design is one of the viable solutions to this problem. The project will allow the student to develop simulation and prototyping skills for these converters with the state-of-the-art semiconductors in the market. This is a good step on the road for a light-weight-based vehicle, thus extending the range of these vehicles.

Student roles:
Simulation and modeling

Skills required:
Third Year Electrical Engineering Student

Research area: The main research area is Smart Electric Grids including the following research themes: 1- Power quality and data analytics. 2- Smart distribution system design, management and optimization. 3- Renewable energy and distributed generation integration. 4- Transportation electrification 5- Energy monitoring/management and smart metering. 6- Asset management and optimization. 7- Microgrid

Student roles:
Student is expected to be working on monitoring the power and energy in smart grid systems and will perform power quality assessment and perform compliance testing to power
quality benchmarks and technical standards.

Skills required:
Basic knowledge of electric circuits/power.

Research area: We work on projects related to transportation electrification mainly.

Student roles:
Modeling and simulation

Skills required:
High GPA Third year electrical engineering student

Research area: Printed electronics and sensors

Student roles:
Students participating in this project will be involved in every stage of sensor development, from conceptualization to performance evaluation. Initially, they will conduct a thorough literature review to understand the current state-of-the-art in printed pressure sensors and their medical applications, with a focus on respiration monitoring and wearable health technologies. Students will then select and formulate suitable functional inks—such as piezoresistive, piezoelectric, or triboelectric composites—optimizing their rheological properties for precise 2D printing onto flexible substrates.
During the fabrication phase, students will design sensor patterns, operate printing equipment, and fine-tune printing parameters to achieve ultrathin, skin-conforming devices. They will also develop and implement protocols for integrating these printed sensors with electronic readout systems, ensuring reliable signal acquisition and data transmission. Special attention will be given to sensor calibration and the development of wireless or remote monitoring capabilities, simulating real-world medical scenarios.
Testing and characterization will involve applying controlled mechanical stimuli to the sensors and measuring their response in terms of sensitivity, linearity, repeatability, and durability. Students will compare sensor performance to clinical standards, such as spirometers, and analyze data to assess the suitability of the devices for continuous patient monitoring.
Throughout the project, students will document their methods, troubleshoot fabrication and integration challenges, and iterate on their designs based on experimental outcomes. They will work collaboratively, dividing tasks efficiently and communicating findings through presentations and written reports. By the end of the project, students will have gained valuable hands-on experience in printed electronics, sensor integration, and biomedical device development, equipping them with practical skills and insights relevant to careers in medical technology and advanced materials research.

Skills required:
Students should have a background in chemistry, materials science, biomedical or electrical engineering, or a related discipline, with familiarity with chemical materials, passion for sensor technology, and additive manufacturing. Critical thinking, analytical and problem-solving skills are essential, as is the ability to work collaboratively in a laboratory setting. Effective communication and documentation abilities will be important for sharing results and integrating feedback throughout the design and testing process.

Research area: I have been pioneering research in quantum optics and quantum foundations for 26 years, with a focus on the quantum properties of light and the nature of quantum measurement. Using single photons and entangled photon states, we investigate foundational questions such as the meaning of the wavefunction, how measurements disturb quantum systems, and how information can be optimally extracted from quantum states. Our work combines experimental photonics with theoretical modelling and overlaps with quantum information and quantum metrology. Students may participate in laboratory experiments, theoretical calculations, or a combination of both depending on their interests and background.

Student roles:
The student will participate in both the theoretical and experimental aspects of the project as part of a collaborative research team. Early in the internship, the student will complete background reading and prepare a bibliography summarizing relevant research literature. They will then assist in developing theoretical models and identifying key experimental parameters.

Depending on the direction of the project, the student may help design and assemble optical experiments using lasers, optical fibers, and single-photon detectors. Experimental tasks may include optical alignment, data acquisition, troubleshooting, and data analysis. Students interested in theory may focus more heavily on modelling quantum measurements and numerical simulations.

The project includes regular meetings with the supervising professor and interactions with graduate student mentors in the laboratory. The student will maintain organized research notes, code, and documentation throughout the internship.

Expected milestones include:

Literature review and annotated bibliography
Development of theoretical framework and experiment plan
Construction and testing of the experimental setup
Data collection and analysis
Final research notebook and presentation materials

The final deliverables will include documented theory, experimental procedures, analyzed data, and associated code and notes.

Skills required:
The student should have completed an undergraduate course in quantum physics and be familiar with Dirac bra-ket notation and basic quantum mechanics calculations. Background knowledge in optics, electromagnetism, linear algebra, or photonics would be helpful. Programming experience in Python, MATLAB, or similar scientific software is beneficial but not required. Prior laboratory experience is also beneficial but not necessary. The project is suitable for students interested in quantum physics, photonics, and experimental or theoretical research.

Research area: My current research is centered in the general areas of solid-state electronics and photonics with particular attention to apply nanomaterials and micro-/nanofabrication for next-generation electronic, photonic, and optoelectronic devices. The research projects include design, fabrication, and characterization of colloidal quantum dot (QD) and cellulose nanocrystal based electronic and photonic devices, as well as micro-/nanostructured devices for sensing and energy harvesting.

Student roles:
Throughout the project the student will be part of a research team led by a senior PhD student, but he/she is also expected to work independently on each of the assigned tasks. The student will carry on literature review of relevant research topics, and work on one or more of following tasks:
i) Design the QD-on-Si device and simulate its photonic performance;
ii) Fabricate and characterize QD-on-Si devices;
iii) Analyze experimental results and provide feed-back to modelling works.

Skills required:
Background
- Senior undergraduate student in Electrical Engineering, Physics, Material Science and Engineering
- Background in semiconductor materials and optoelectronics
- Knowledge of general physics, chemistry, and electronics
- Knowledge/interest on experimental research

Skills
- Team work
- Good communications skills
- Experience in FDTD simulation or characterization of optoelectronic and photonic devices is preferred

Research area: Our research group specializes in the design, fabrication and testing of specialty optical fibers and photonic devices for applications in optical communications and optical sensing. The domains of research and applications also extend to quantum technologies and biomedical sensors.

Student roles:
The intern will learn how to use quantum optical devices (optical fibers, prisms, waveplates, etc.) and perform a number of experiments (described above). The intern will report to the supervisor by means of in-person meetings (1/week), written weekly reports and technical reports.

Skills required:
- Experience and proficiency with laboratory instruments (e.g. oscilloscope, etc.)
- Basic knowledge of quantum physics/quantum mechanics
- Good communication skills
- Ability to work inside a team

Research area: Interdisciplinary areas of applied electromagnetics and wireless communications, with a particular focus on the development of high-performance computational models/algorithms for emerging wireless technologies in 5G/6G/THz wireless communications, intelligent transportation (air, ground, underground), underwater communications, industrial Internet of Things, as well as biomedical sensing and healthcare applications. Keywords: Applied Electromagnetics, 5G/6G Wireless, Integrated Sensing & Communication, Localization, Antennas & RF/Microwave Design, Machine Learning & Parametric Modeling, Stochastic Uncertainty Quantification, Internet of Things & Intelligent Systems.

Student roles:
(1) Assisting in conducting literature reviews to gather relevant research papers, articles, and other academic resources to support the research project.
(2) Collaborating with the research team to exchange ideas, share knowledge, and contribute to the overall research goals, including methodology & model development, results analysis, etc.
(3) Participating in group meetings, and effectively communicating project progress and results.
(4) Keeping records of research procedures, observations, and findings. Writing reports, summaries, and contributing to scientific papers writing or presentations.

Skills required:
The project suits students with interests and background in ML/AI, mathematics, electromagnetics or communication theory, and programming.

Research area: Electric machines, motor drives, and advanced propulsion systems for sustainable aviation. Research focuses on rare-earth-free motor technologies, including switched reluctance and synchronous reluctance machines, advanced control strategies, power electronics integration, electromagnetic design optimization, and real-time simulation. The goal is to develop lightweight, efficient, reliable, and sustainable electric propulsion systems that reduce dependence on critical materials while meeting the stringent performance requirements of future electric aircraft, eVTOL platforms, and aerospace applications.

Student roles:
The student will conduct literature reviews, develop machine models, perform electromagnetic simulations, analyze motor performance, and assist in developing control strategies for rare-earth-free propulsion systems. Responsibilities include implementing simulation studies, validating results, documenting findings, participating in research meetings, and preparing technical reports and presentations. The student will collaborate with graduate researchers and gain exposure to cutting-edge research in electric aviation and advanced propulsion technologies.

Skills required:
Candidates should have a background in electrical engineering, mechatronics, aerospace engineering, or a related discipline. Knowledge of electric machines, electromagnetics, power electronics, control systems, and MATLAB/Simulink is desirable. Experience with finite-element analysis tools such as ANSYS Maxwell, JMAG, or Motor-CAD is beneficial but not required. Strong analytical, programming, and problem-solving skills are preferred. Students interested in sustainable aviation, electric propulsion, and advanced motor-drive technologies are encouraged to apply.

Research area: Mohamed Lamine Fayçal Bellaredj a obtenu le diplôme d'ingénieur en électronique et le magister en physique de l'Université des Sciences et Technologies d'Oran (USTO), Bir El Djir, Algérie, respectivement en 2005 et 2007, ainsi que le doctorat. diplôme en micro-ingénierie de l'Université de Franche-Comté, Besançon, France, en 2013. Ses intérêts de recherche incluent l'acoustofluidique, les ondes acoustiques de surface et les dispositifs acoustiques à base de métamatériaux, l'ingénierie passive embarquée pour l'électronique RF, numérique et de puissance, l'hybride flexible. électronique (FHE), micro-ingénierie/nano-ingénierie, modélisation, fabrication et caractérisation de systèmes MEMS/nanoélectromécaniques (NEMS), physique et technologie des dispositifs à semi-conducteurs et cellules solaires

Student roles:
Revue bibliographique
Conception et fabrication
Rédaction de rapports et de publications (encouragée)

Skills required:
Formation en ingénierie électrique, sciences des matériaux, physique etc.

Research area: Towards sixth-generation networks (6G), satellite communication systems, especially based on Low Earth Orbit (LEO) networks, become promising due to their unique and comprehensive capabilities. These advantages are accompanied by a variety of challenges such as security vulnerabilities, management of hybrid systems, and high mobility. The project targets secure communication system design in emerging LEO satellite networks, both from terrestrial Earth gateways and the inter-satellite links (ISLs). The potential of the machine learning-based approaches for attack detection will be investigated.

Student roles:
The following roles are expected:
1. Performing a literature survey.
2. Understanding the mathematical model for the satellite communications.
3. Designing a simulation framework for the performance evaluation.
4. Investigation of potential jamming threats in satellite networks.
5.Testing the performance of learning-aided solutions for detection of jamming attacks.
6. Reporting the research outputs in terms of journal and/or conference paper.

Skills required:
Probability theory,
Communication system theory,
Basic programming skills (including MATLAB).

Research area: I am the founder and director of the ECCoLe Lab (Edge Computing, Communication, and Learning) at INRS-EMT. Our research focuses on efficient AI computing and wireless communication systems, combining expertise in computer architecture, embedded systems, machine learning, and wireless signal processing. Our main activities include: (1) energy-efficient hardware accelerators for deep learning; (2) lightweight AI techniques for wireless communications; and (3) optimization of deep learning models for real-time edge deployment. ECCoLe promotes a highly interdisciplinary environment bridging AI algorithms with practical hardware and communication system implementations. To learn more about our projects and research activities, please visit our website: https://inrs-eccole.github.io/index.htm

Student roles:
The intern will participate in the design and evaluation of an AI-based wireless communication receiver using NVIDIA Sionna. The main objective of the project is to investigate self-supervised deep learning techniques for signal demodulation in OFDM wireless systems under realistic channel conditions.

The intern will first become familiar with the Sionna simulation framework and wireless communication fundamentals, including modulation, OFDM transmission, channel models, and conventional demodulation methods. They will then develop simulation environments for different wireless scenarios, such as AWGN and fading channels, and generate datasets for training and evaluation.

A key part of the internship will involve implementing and training neural-network-based demodulators using self-supervised learning approaches. The intern will explore techniques such as pilot-assisted learning, pseudo-labeling, and consistency-based training to reduce the need for fully labeled data. The developed models will be evaluated and compared against conventional communication receivers in terms of bit-error rate (BER), robustness to channel variations, and computational complexity.

Throughout the project, the intern will gain hands-on experience in machine learning, wireless signal processing, and AI-assisted communication system design. The internship will also provide exposure to modern research methodologies, including experiment design, performance analysis, and scientific reporting.

At the end of the internship, the student is expected to deliver a documented simulation framework, performance evaluation results, and a final technical report summarizing the developed methods and findings. Depending on the achieved results, the work may contribute to future conference or journal publications within the ECCoLe research team.

Skills required:
The ideal candidate should have a background in electrical engineering, computer engineering, computer science, or a related field. Basic knowledge of wireless communication systems, digital signal processing, and machine learning is recommended. Experience with Python programming and familiarity with deep learning frameworks such as TensorFlow or PyTorch are important assets. Prior exposure to wireless simulation tools, OFDM systems, or neural networks is beneficial but not mandatory. The student should be motivated to learn interdisciplinary topics at the intersection of AI, wireless communications, and embedded computing.

Research area: Quantum technologies are advancing scientific research and technological innovation worldwide by enabling end-to-end security, enhanced resilience, and efficient communication systems. This project sits at the intersection of quantum communication and space-air-ground integrated networks (SAGIN), a three-layer architecture comprising satellite, aerial (uncrewed aerial vehicle (UAV)/high-altitude platform station (HAPS)), and terrestrial network layers. Research in this area addresses the integration of quantum key distribution (QKD) and entanglement-based protocols into heterogeneous, dynamic network topologies under realistic operational constraints.

Student roles:
The following roles are expected:
1. Performing a literature survey on quantum communication and SAGIN integration.
2. Understanding and contributing to the mathematical system model for quantum-SAGIN communication.
3. Designing a simulation framework for performance evaluation under realistic SAGIN constraints.
4. Contributing to the design or analysis of QKD protocols or handoff strategies across SAGIN layers.
5. Testing and benchmarking proposed methods through simulation.
6. Reporting research outputs through a technical report and, where possible, a journal or conference paper contribution.

Skills required:
Probability theory and stochastic processes
Communication system theory (wireless channels, modulation, coding)
Strong mathematical and analytical problem-solving abilities
Basic programming skills (MATLAB and/or Python)
Basic knowledge of quantum information or quantum communication (an asset)
Familiarity with network modeling or simulation tools (an asset) •

Research area: We investigate superconducting quantum devices (SQDs). SQDs are superconducting nanostructures operated at temperatures in the tens of milliKelvin range that exhibit quantum effects, such as energy level quantization and state superpositions. SQDs can be used to implement qubits, which are two-state quantum systems used to store and process quantum information. Superconducting qubits are presently one of the main candidate systems for the implementation of quantum computing. SQDs are also important components of many quantum sensors. Besides these applications, SQDs are relevant for fundamental explorations in light-matter interaction and dynamics of open quantum systems.

Student roles:
The student will join a team formed of ten graduate students and three postdoctoral researchers working on various aspects of SQDs. The student will have the opportunity to contribute to both theoretical and experimental aspects of the proposed research.
Specific possible tasks in the project will include:
- Electrical tests of devices. Such tests involve room temperature and/or low-temperature electrical characterization;
- Design and implementation of control pulses for optimal quantum state manipulation. The student will develop and program suitable pulse sequences, building on an already established environment for instrument control;
- Data acquisition and analysis. Data analysis will be done using software such as Python, Mathematica, and other tools;
- Modelling and numerical simulations of device dynamics. This work will be used to analyze new concepts relevant for experimental designs or to analyze results of experiment. The work will use models of quantum dynamics, based on master equations. The student will build on established models and do numerical studies using Ptyhon and/or Mathematica; and/or
- Electromagnetic modeling. Electromagnetic simulations using analytical tools and finite element analysis are a central tool to extract the parameters of devices.
The project will provide an excellent opportunity for learning, as the range of experimental and theoretical methods is very broad. In addition to learning theoretical methods in quantum control and experimental techniques in electronics and low-temperature physics, the student will become familiar with device nanofabrication. This range of skills is highly relevant for a wide range of academic and industry career paths.

Skills required:
The student will have a background in physics or engineering. Courses on the following topics are relevant to the proposed research: quantum mechanics, electromagnetism, solid-state physics, analog and digital electronics, microwave engineering, and software development. While not all these courses are required, the more of these courses are taken, the higher the chance for the student to benefit from and contribute to this project.
Prior experience with laboratory work is important, in particular if it involves electronics, electronic instrumentation, and/or low-temperature physics.

Research area: Dr. Fang's research interests mainly focus on advanced drive systems toward transportation electrification, especially the advanced control of switched reluctance machines and permanent magnet synchronous machines. Dr. Fang was named on the World's Top 2% of Scientists and Engineers list by a Stanford University study. Dr. Fang also serves as an Associate Editor of IEEE Transactions on Transportation Electrification.

Student roles:
The student will mainly focus on simulation and experimental investigation to compare the impact of position sensor type on motor drive performance.

Skills required:
The undergraduate applicant should currently be enrolled in the Engineering discipline and be proficient in English.

Research area: Mes principaux domaines d'intérêt sont les antennes intelligentes, les circuits et systèmes micro-ondes et en bandes millimétriques, les méthodes numériques en électromagnétisme, les matériaux électromagnétiques artificiels, les radars, et les applications biomédicales.

Student roles:
Sous la supervision du professeur, l'étudiant ou les étudiants ajusterons des paramètres des programmes informatiques et développerons leurs propres programmes informatiques pour optimiser les résultats la détection. L’étudiant ou les étudiants feront également des tests du système selon différents scénarios.

Skills required:
L'étudiant doit être familiarisé avec les bases de l'électronique (amplificateur, filtre, circuits sur breadboard) et la programmation informatique (C Sharp, Matlab etc.).

Research area: Terahertz technologies use frequencies between 0.1-10 THz. Terahertz is able to pass through solid objects and image within and beyond objects. Such systems make use of specialized emitters and detectors to measure these low-photon-energy electromagnetic waves. Terahertz is used in a wide range of applications, including biomedical, non-destructive testing, and communications.

Student roles:
The students will perform research on a new imaging technology for terahertz. The work will refine polarization-specific single-pixel imaging in terahertz. The students will assemble and characterize a system that extends traditional terahertz single-pixel imaging into polarization-specific single-pixel imaging. The students will develop the system through several key phases. In Phase I, over weeks 1-4, the students will design the system using knowledge of optics and electric circuits. This will involve selecting and characterizing the components for physical separation of the different pixels. In Phase II, over weeks 5-8, the students will build the system based on the selected diffractive components and instrumentation integration. This instrumentation integration will involve development of the initial prototype. In Phase III, over weeks 9-12, the students will apply the system for nominal tests. These nominal tests will be on representative samples (e.g., high impact polystyrene samples) for characterization in terms of non-destructive testing application. The proposed work is an important pilot-project which will enable further projects in the School of Engineering at the University of British Columbia. The work will be suitable for the experience level of an undergraduate student. The students will be provided with hands-on experience in engineering design and academic research. It is envisioned that the work can be disseminated through articles in relevant journals (e.g., Applied Optics or Optics Letters).

Skills required:
The ideal candidate will have experience with electrical engineering or physics. Experience with electrical circuits, electromagnetics, and optics (Snell's law, Fresnel conditions, etc.) in both an experimental and theoretical context is desirable. It will also be an asset to have experience trouble shooting both software and hardware, as this will be required for the development and characterization of the system. As the students will be working in a team environment, strong leadership and teamwork abilities are desirable. As the work will be disseminated through presentations and journal articles, strong oral and written communication skills would be ideal.

Research area: This proposed research project is to conduct a preliminary study on the development of an environment-friendly and cost-effective renewable energy harvesting technique by using innovative triboelectric nanogenerators (TENGs), a new type of energy harvesters especially good at converting small-scale mechanical motions into electricity. It can build highly efficient low-cost general-purpose renewable energy harvesters, which would make no negative impact on the environment. Featuring a small footprint, the developed TENG unit device is expected to be robust, portable, cost-effective, assemblable for large scale, and fit for mass production. It can be also used for autonomous sensing applications.

Student roles:
The student will work with my graduate (mostly PhD) students in a team

Skills required:
Electrical or computer engineering background, power electronics, instrumentation, prototype construction and measurement preferred

Research area: Dr. Jinyang Liang is currently directing the Laboratory of Applied Computational Imaging (LACI, www.jinyangliang.com). His research focuses on implementing optical modulation techniques to develop new optical instruments for applications in biology and physics. Currently, his laboratory is working on the following three directions : 1. Compressed ultrafast photography (CUP)—the world’s fastest receive-only camera with a real-time imaging speed of up to 10 trillion frames per second. 2. Band-limited illumination profilometry (BLIP)—a coded-aperture-imaging-based laser modulation technique for high-speed 3D surface imaging. 3. Single-pixel imaging accelerated by swept aggregate patterns (SPI-ASAP)—an ultrahigh-speed general-purpose single-pixel camera.

Student roles:
The required role of the intern(s) is manifested in the following three aspects.
First, the intern(s) will diligently study the new knowledge in both hardware and software that is associated with the assigned research tasks (see details in the previous section), during the entire duration of this internship. He/She needs to report the progress on a bi-weekly basis, discuss the ongoing problems, search for possible solutions, and present the plan. The goal of this training is to develop the intern(s) into independent researchers with creative thinking ability. The internship will also endow the intern(s) with skills that are highly marketable for the next stage of their career in either industry or academia.
Second, the intern(s) will need to frequently and effectively communicate with other group members, especially the graduate students and/or postdoctoral fellows who will directly guide their research tasks. In addition, the student(s) will assist in integrating their research achievements into the optical imaging systems that are under development. The goal of this training is to develop the intern(s) teamwork skills in problem-solving and troubleshooting.
Finally, at the end of the internship, a written report that summarizes all the achievements is required. The intern(s) will need to include all the generated knowledge and technical know-how (including the source code) as attachments. It is critically important for the intern(s) to transfer their completed research tasks to other lab members who will be taking over their research in the future.

Skills required:
Applicants should be enrolled in an undergraduate major in Electrical Engineering, Automation Control, Optical/Optoelectronic Engineering, Physics, or a related field. Preferences will be given to candidates with a strong background in applied optics, physical optics, digital/analog electronics design, system automation, and control (using LabVIEW interface), imaging reconstruction and processing (using Matlab and C++), biology, and/or acoustics. Previous internship experience in a research laboratory is highly desired. Proficiency in English (e.g., TOEFL, IELTS, and/or GRE scores) is a plus. Experience in optical design software (e.g., Zemax or CodeV) is a plus, but not necessary.

Research area: The devices are simple metal-insulator-metal structures at a thickness of only a few nanometers insulating layer, which allows for quantum mechanical tunnelling. Students should be familiar with e.g. a quantum well

Student roles:
The student will actively participate in our research activities on a day to day routine, the student will receive a comprehensive safety training as well as a training on all relevant laboratory equipment to then join the team to participate in all group activities.

Skills required:
Students should be curious more than anything else. We can capitalize on a large variety of skills, whether a candidate enjoys film deposition, structural and functional characterization as well as numerical simulations with e.g. finite element or DFT tools

Research area: Printed electronics and sensors

Student roles:
Students in this project will be central to the conception, fabrication, and validation of the wearable fatigue sensors. Their journey begins with a review of the latest advances in sweat biomarker detection, microfluidic integration, and wearable EMG technology. Under expert supervision, students will formulate and print functional inks for biochemical sensing, design microfluidic channels to manage sweat flow and prevent air bubble interference, and fabricate soft, stretchable electrodes for capturing muscle activity. They will optimize sensor layouts for comfort, adhesion, and data fidelity, ensuring the patches remain robust during vigorous movement.
The integration phase will see students assembling the multimodal sensor system, combining biochemical, biomechanical, and environmental sensing elements into a single flexible device. They will develop protocols for sensor calibration, real time data acquisition, and wireless transmission to a mobile platform. Collaborating with peers in computer science or data analytics, students will help implement AI based algorithms that analyze sensor data, identify fatigue patterns, and generate personalized feedback or alerts.
Testing will involve both controlled laboratory experiments and real world trials with volunteers engaged in athletic or rehabilitation activities. Students will compare sensor outputs to gold standard laboratory measurements, assess usability and comfort, and iterate on designs based on user feedback. They will document their processes, troubleshoot technical challenges, and present findings in group meetings and reports, developing skills in scientific communication and interdisciplinary collaboration.

Skills required:
Students should have a foundation in chemistry, material science, chemical engineering, biomedical engineering, electrical engineering, or computer science, with hands on experience in sensor technology, microfabrication, wearable electronics or AI supported acquisition systems. Skills in data analytics or machine learning for interpreting physiological signals will be advantageous. A keen interest in sports science, health monitoring, and interdisciplinary teamwork is essential. Students should be comfortable working with chemicals and electronic devices, possess strong problem solving and communication skills, and be eager to contribute to the next wave of wearable health technologies.

Research area: Array signal processing, working with radio signals received by the Long Wavelength Array https://leo.phys.unm.edu/~lwa/index.html

Student roles:
Learn to run existing Python code on a high speed computer cluster that finds the azimuth and elevation for a given signal. Add functions to the code to accomplish the goals of the research project.

Skills required:
python programming,
GNURadio programming,
Digital signal processing concepts,

Research area: I have more than 10 years of research experience in signal processing for wireless communications. Over this period, I have authored or co-authored more than 100 peer-reviewed papers in IEEE journals and conference proceedings. My work has received more than 7000 citations, and I currently have an h-index of 42. Over the past six years, I have published extensively in leading IEEE journals and major conferences, including ICC. In addition, I have received two NSERC Alliance grants in quantum communications, which reflect both the quality of my research and my growing contributions to this emerging area.

Student roles:
The student will play an active role in supporting the research activities of the project from both the theoretical and practical sides. The main role of the student will be to help study and develop secure wireless communication systems that combine quantum communication with OTFS modulation for future 6G networks. This will include reading and understanding related research papers, learning the basic principles of Continuous-Variable Quantum Key Distribution (CV-QKD), and becoming familiar with OTFS-based wireless system models.

The student will assist in building mathematical models and simulation frameworks for the proposed communication systems. They will help test receiver algorithms, channel estimation methods, and coding techniques to evaluate system performance under different wireless channel conditions. The student will also support the analysis of results, prepare figures and summaries, and contribute to technical discussions during the project.

In addition, the student will take part in regular research meetings and will be expected to communicate progress clearly. As the project includes a strong training component, the student will also have opportunities to improve research, communication, and collaboration skills. They may contribute to writing reports, presentations, and possibly research papers. Overall, the student’s role is to support the development, analysis, and evaluation of new quantum-secure 6G communication methods while gaining strong research experience in wireless communications and signal processing.

Skills required:
The student should have a good background in wireless communications, signal processing, and basic mathematics for communication systems. Knowledge of digital communications, probability, and linear algebra will be helpful. Familiarity with OFDM, OTFS, or channel estimation is an advantage. Some background in quantum communication is useful, but not required, as long as the student is willing to understand and learn new concepts during the project. The student should also have programming skills, especially in MATLAB or a similar simulation tool, since the work involves system modelling and analysis. Good problem-solving skills, research interest, and willingness to learn are also important.

Research area: Mohamed Lamine Fayçal Bellaredj a obtenu le diplôme d'ingénieur en électronique et le magister en physique de l'Université des Sciences et Technologies d'Oran (USTO), Bir El Djir, Algérie, respectivement en 2005 et 2007, ainsi que le doctorat. diplôme en micro-ingénierie de l'Université de Franche-Comté, Besançon, France, en 2013. Ses intérêts de recherche incluent l'acoustofluidique, les ondes acoustiques de surface et les dispositifs acoustiques à base de métamatériaux, l'ingénierie passive embarquée pour l'électronique RF, numérique et de puissance, l'hybride flexible. électronique (FHE), micro-ingénierie/nano-ingénierie, modélisation, fabrication et caractérisation de systèmes MEMS/nanoélectromécaniques (NEMS), physique et technologie des dispositifs à semi-conducteurs et cellules solaires

Student roles:
Revue bibliographique
Conception et fabrication
Rédaction de rapports et de publications (encouragée)

Skills required:
Formation en ingénierie électrique, sciences des matériaux, physique etc.

Research area: Einstein à créé la théorie de la relativité restreinte dans le cadre de son étude de l'électromagnétisme pour les corps en mouvement. En utilisant la méthode des différences finies dans le domaine temporel (FDTD, Finite Difference Time Domain) pour la résolution des équations de Maxwell, il est possible de traiter des problèmes complexes en électromagnétisme avec des corps en mouvement.

Student roles:
Développer un code informatique sur Matlab, traiter différents signaux, représenter les résultats après transformation en ondelettes.

Skills required:
Principales compétences:
- programmation Matlab
- bases en signaux temporels
- génie électrique