Research Associate In Dexterous Manipulation And Robot Learning

Are you a robot learning researcher eager to push the boundaries of dexterous manipulation? Join Dex Lab at Imperial College London, led by Dr. Rolandos Potamias and Stefanos Zafeiriou, in a postdoctoral research role to lead transformative projects spanning robot foundation models and real-world dexterous manipulation.

Dex Lab at Imperial is seeking a highly motivated and talented Postdoctoral Research Associate (PDRA / Post Doc) who has demonstrated competence in conducting cutting-edge robot learning research. The position focuses on building dexterous, high-degree-of-freedom (high-DoF) manipulation policies and robot foundation models, such as vision-language-action models (VLAs), learned from human demonstrations, but is not limited to this. The successful candidate will work on a state-of-the‑art robotic platform comprising Sharpa Wave dexterous hands and UR7e arms, contributing both to methodological advances and to the deployment of learned policies on real robots.

To this end, the role integrates knowledge from robot learning, computer vision, generative modelling and control.

The post will focus on research topics in probabilistic programming. The specific details of the project are flexible and will be determined based on the interests and strengths of the successful candidate.

You will conduct original research at the intersection of dexterous manipulation, robot learning and foundation models, exploring how large‑scale human demonstration data (., video, motion capture and teleoperation) can be turned into capable, general‑purpose robot behaviour. In particular, you will develop novel algorithms and policies for high‑DoF hands and validate them on real hardware. In doing so, you will collaborate with a team of expert researchers in robotics, computer vision and machine learning.

We strive to publish in top‑tier conferences such as CVPR, NeurIPS, ICLR, ECCV, ICCV, ICRA and RSS.

• A strong track record in top conferences and journals in robot learning, machine learning or computer vision such as CVPR, NeurIPS, ICLR, ECCV, ICCV, ICRA and RSS.
• Demonstrated robot learning experience (., imitation learning, learning from demonstrations, VLAs / robot foundation models, or reinforcement learning) is a must.
• Strong PyTorch programming skills and working knowledge of ROS are a must.
• Hands‑on experience deploying learned policies on real robots is a must; experience with dexterous hands, teleoperation or motion capture for demonstration collection is a plus.
• Applicants must hold a PhD in computer science, robotics, engineering or equivalent.

You should have proven research record and publications in the relevant areas.

Please see job description for a full list of requirements.

• The chance to work in an exciting and rapidly developing area, with access to state‑of‑the‑art hardware including Sharpa Wave hands and UR7e arms. This is a chance to grow and establish yourself as a leader in this field.
• Dedicated mentorship as well as the freedom to explore your own ideas.
• Working closely with a team of PhD students and postdocs from different backgrounds.
• The Department of Computing is the top‑1 ranked computer science department in the UK, according to .
• Sector‑leading salary and remuneration package (including 43 days off a year).
• Disseminating your research in major robotics, machine learning and computer vision conferences is supported and travel costs will be covered.