Join an interdisciplinary research team to advance smart sensor systems and Edge AI at a leading university. You will work on cutting-edge projects in embedded machine learning and autonomous robotics, while also contributing to teaching and mentoring students.

• Design, prototype, and validate intelligent embedded systems using novel sensors, such as event-based cameras, optical flow sensors, UWB for positioning, depth cameras, and low power radars
• Conduct research in embedded machine learning, with focus on attention-based models, neuromorphic computing, TinyML, EdgeAI, and real-time embedded signal processing
• Apply techniques like quantization, pruning, knowledge distillation, and develop new architectures beyond CNNs for resource-constrained systems
• Support and contribute to teaching activities, including project-based learning and mentoring student projects
• Assist in supervising students, including PhD candidates
• Coordinate lab activities and participate in preparing research proposals and grant applications
• Lead and co-author publications in top journals and conferences

• PhD in Electrical Engineering or Computer Engineering
• Deep expertise in system-level design with ability to develop hardware/software prototypes; PCB design is a plus
• Strong knowledge of machine learning algorithms, including spiking networks, and compression techniques for real-time embedded platforms
• Experience in hardware-software co-design for embedded and neuromorphic platforms
• Track record of publishing in top IEEE journals or major robotics and machine learning conferences
• Enthusiasm for teaching, mentoring, and supporting project-based learning

• Dynamic and interdisciplinary research environment
• Opportunities to collaborate on innovative prototypes and real-world applications
• Access to a strong academic and industrial network in robotics, embedded AI, and sensing technologies
• Inclusive and diverse workplace that values equality and sustainability