Imperial College London
Research Associate in Dexterous Manipulation and Robot Learning
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Job number: ENG04060
Salary or Salary range
£50,733 - £59,484 per annum
Posting End Date
4 Nov 2026
About the role
Are you a robot learning researcher eager to push the boundaries of dexterous manipulation? Join DexLab 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.
DexLab at Imperial is seeking a highly motivated and talented Postdoctoral Research Associate (PDRA / PostDoc) 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.
What you would be doing
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 (e.g., 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.
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What we are looking for
- 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 (e.g., 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.
What we can offer you
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- 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 REF 2021.
- 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.
Further information
Full-time, fixed term position for 12 months to start as soon as possible
*Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range £45,399 - £48,876 per annum.
In addition to completing the online application candidates should attach:
- A full CV with a list of all publications
- A research statement indicating what you see are interesting research issues relating to the above post and why your expertise is relevant
Informal enquiries related to the position should be directed to Dr Rolandos Potamias r.potamias19@imperial.ac.uk
For queries regarding the application process contact Jamie Perrins: j.perrins@imperial.ac.uk
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