Postdoc Bridging Physics and Machine Learning for the Control of Soft Robots

Contribute to pioneering robotics research in bridging physics and machine learning for the control of continuum soft robots

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.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty Mechanical Engineering

From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to understand our environment and discover its underlying mechanisms, research and education at the ME faculty focusses on fundamental understanding, design, production including application and product improvement, materials, processes and (mechanical) systems.

ME is a dynamic and innovative faculty with high-tech lab facilities and international reach. It’s a large faculty but also versatile, so we can often make unique connections by combining different disciplines. This is reflected in ME’s outstanding, state-of-the-art education, which trains students to become responsible and socially engaged engineers and scientists. We translate our knowledge and insights into solutions to societal issues, contributing to a sustainable society and to the development of prosperity and well-being. That is what unites us in pioneering research, inspiring education and (inter)national cooperation.

Conditions of employment

• Duration of contract is 7 months.
• A job of 36-40 hours per week.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.