PhD Position Physics-informed Foundation Models for Robotics

Develop physics-informed techniques for the next generation of robotic foundation models!

In big tech, a race is underway to collect as much robotic data as possible, with the goal of training the ChatGPT of robotics physical intelligence. But physical data are much harder to get than language examples!

We are looking for a PhD candidate to join the Physical Intelligence Lab at TU Delft and contribute to the development of physics-informed foundation models for robotic manipulation. The position is part of the ambitious European project GRAIL, which aims to extend the paradigm of foundation models to systems interacting with the physical world; let’s build the first European foundation model for robotics together!

The PhD candidate will help solve the robotic data gap by developing learning architectures that integrate physical structure from mechanics and dynamical systems into modern machine learning frameworks. This way, the models will not have to learn physics from data every time and will be able to focus only on what is actually new. The work will involve developing representations that enable generalization across tasks, environments, and robotic platforms, with particular attention to deformable media and compliant manipulation.

The candidate will be supervised by Dr. Della Santina and work within a collaborative research environment spanning control theory, machine learning, and (soft) robotics, with access to experimental platforms and collaborations across the European consortium. The consortium will include AI&Robotics companies and world experts in deep learning from all over Europe.

• First and foremost: scientific curiosity and passion! (must have)
• MSc in computer science, robotics, mechanical engineering, applied mathematics, physics, computer engineering or related field (must have - fine if not achieved yet, but close to completion)
• Strong background in deep learning
• Familiarity with nonlinear dynamics and modeling mechanical/physical systems
• Strong programming skills in Python and PyTorch
• Experience with ROS and ROS2 is a plus
• Proficiency in written and spoken English (must have)
• Prior experience in machine learning for control, soft robotics, robot manipulation, or other forms of experimental robotics is a plus

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1.5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2.5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3059 - €3881 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

Faculty/Department: Faculty of Mechanical Engineering

FTE: 1.0

Submission is possible until: 9 Jun 2026