JOB DESCRIPTION

We seek a postdoctoral researcher for a project on bridging physics and machine learning for the control of mechanical systems, and specifically of soft robots. This role involves advancing theoretical models and methods and validating these approaches in simulation and in lab experiments - with the ultimate goal being establishing provably stable, compliant, and interpretable controllers based on learned models that generate simultaneously precise and safe robotic behavior.
Candidates should have a robust background in soft robotics, control theory, nonlinear dynamics, and machine learning. Publications in these fields are a strong advantage.
We aim to offer a platform for researchers to grow in a multidisciplinary and supportive environment. This position will allow you to grow as a researcher, preparing you for different aspects of your next steps in the academic journey. Your responsibility will include coordinating project activities, including supervising master’s students and mentoring junior Ph.D. students, ensuring a collaborative and productive research environment. You will have the opportunity to interact with stakeholders in and out of academia and see your developments applied in real-world contexts

JOB REQUIREMENTS

The candidate needs to have:

• Ph.D. degree (awarded or close to completion) in Robotics, Control Theory, Computer Science, Applied Mathematics, or a closely related field.
• Proven experience in autonomously managing professional responsibilities (examples: teaching, research, interaction with third-party stakeholders, guiding MSc students).
• Fluent communication skills in English, both written and oral.
• An outstanding academic track record with publications in top-level academic conferences (e.g., RSS, RoboSoft, NeurIPS, ICLR) and journals (e.g., T-RO, RA-L, L-CSS).
• Prior research experience in soft robotics and machine learning.

The candidate ideally also:

• Has experience in modeling and controlling soft robots.
• Is proficient in modern machine learning frameworks (e.g., PyTorch, JAX)
• Is comfortable with carrying out experimental work.
• Is familiar with nonlinear systems theory.

Please refer the Job description for details