PostDoc position: Smart Sensors Systems & Edge AI

We are looking for a highly motivated postdoctoral researcher with a strong background in electrical engineering and hardware-software co-design to join our interdisciplinary research team at D-ITET Center for Project-Based Learning.

The successful candidate will contribute to research at the intersection of embedded machine learning, signal processing, and smart sensing systems, with applications in autonomous robotics, drones, and space technologies. We are particularly looking for a highly motivated researcher with a strong interest and enthusiasm for teaching topics such as embedded systems, machine learning on microcontrollers (MCUs), and FPGA-based design, and who has a genuine passion for project-based learning and mentoring both small and large student projects.

Research Focus:

The postdoctoral researcher will work on the design, prototyping, and validation of intelligent embedded systems that leverage novel sensors, such as:

• Event-based cameras
• Optical flow sensors
• Ultra-Wideband (UWB) for positioning and communication
• Depth camera
• Low power Radars

Key research topics include:

• Embedded Machine Learning (Spiking and non-spiking network) with particular enphasys on attention-based models.
• Neuromorphic computing and ML deployment on digital and neuromorphic processors
• TinyML and EdgeAI and ultra-low-power inference for resource-constrained systems
• Techniques such as quantization, pruning, knowledge distillation, and novel architectures beyond CNNs
• Real-time embedded signal processing for perception and decision-making

While the main focus is on autonomous drones, robotics, and space applications, we are open to exploring additional application domains.

• PhD in Electrical Engineering, Computer Engineering
• Deep expertise in system-level design and the ability to develop functional hardware/software prototypes. PCB design is a plus
• Strong knowledge of machine learning algorithms (including spiking networks) and compression tecniques for real-time processing on embdded platforms
• Experience in hardware-software co-design for embedded and neuromorphic platforms
• Demonstrated ability to publish in top-tier IEEE journals (e.g., IEEE IoT Journal, IEEE Sensors Journal, IEEE Transactions on circuits and systems) and/or
• top robotics and machine learning conferences (e.g. CVPR, ICRA, IROS, NeurIPS)
• A strong publication track record is essential and should clearly reflect your contributions to the field

Additional Responsibilities:

• Support and contribute to teaching activities and student supervision, including PhD Students
• Assist in the coordination of lab activities
• Actively participate in the preparation of research proposals and grant applications
• Lead and co-author high-impact publications