PostDoc position: Smart Sensors Systems & Edge AI

Post Doc position:
Smart Sensors Systems & Edge AI

D-ITET Center for Project-Based Learning is a research and teaching group at ETH Zurich. The group is looking for a talented and motivated postdoctoral researcher to develop the group in both teaching and research on the topics of EdgeAI, Tiny Machine Learning, Embedded System, and Autonomous Robots and Drones. The postdoc position will be hosted in D-ITET department.

Start Date:

as soon as available 2026.

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.

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 emphasis 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 or 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 techniques for real‑time processing on embedded 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.

• 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.

We offer a dynamic, interdisciplinary research environment.

• Opportunities to collaborate on cutting‑edge prototypes and real‑world demonstrators.
• A strong academic and industrial network across robotics, embedded AI, and sensing technologies.

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Sustainability is a core value for us – we are consistently working towards a climate‑neutral future.

If you're passionate about designing intelligent, energy‑efficient embedded systems for impactful real‑world applications, we look forward to receiving your application.

Application materials:

• CV
• Motivation letter explaining why you are the best candidate.

We exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Questions regarding the position should be directed to Dr. Michele Magno (no applications).