PhD Position Physics-informed Foundation Models for Robotics

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

Job description

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 solving the robotic data grap 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 everytime 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.

Job requirements

Below a list of skills that we would be happy to see in a candidate.
Do not be intimidated by it! The must haves are clearly tagged. For all the other points, consider applying even if you do not feel like you satisfy 100% of the requirements.

• 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

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. 

Click here to go to the website of the Faculty of Mechanical Engineering. Do you want to experience working at our faculty? These videos will introduce you to some of our researchers and their work.

Conditions of employment 

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.  

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.  

Additional information

If you would like more information about this vacancy or the selection procedure, please contact Dr. Cosimo Della Santina., via C.DellaSantina@tudelft.nl.

Application procedure

Are you interested in this vacancy? Please apply no later than 9 June 2026 via the application button and upload the following documents:

• CV

• Cover letter (max. 1 page), describing your motivation for applying and fit for the position

• Description of your three most relevant achievements (max. 1 page total)

• Academic transcripts (BSc and MSc, with grades)

You can address your application to Dr. Cosimo Della Santina..

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements. 

Please note:

• You can apply online. We will not process applications sent by email and/or post. 
• As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
• Please do not contact us for unsolicited services.

#EUfunded This is an EU funded project, named GRAIL, with project number 00000, within program HE