We are seeking for highly motivated and talented PhD students to help us on our research on using learning algorithms (deep reinforcement learning, quality diversity optimization, evolutionary algorithms and others) to improve the adaptivity, versatility and autonomy of physical robots. This objective encapsulates several major research directions, including:
- How to learn quickly on a physical robot (Sim-Real transfer)?
- How to learn several skills simultaneously (knowledge transfer)?
- How to learn without the need of roboticists and engineers?
- How to do open-ended life-long learning/adaptation?
The successful candidates will choose the direction(s) that interests him/her the most. The laboratory is currently mainly considering locomotion tasks with legged robots (traversing uneven terrains, climbing stairs, overcoming obstacles, discovering various locomotion modes etc..). However, other robotic applications can be considered.
To apply for this position, you will need to have a strong background in at least one of the following areas:
- Robotics (e.g., forward and inverse models, control theory, model predictive control),
- Machine learning (e.g., deep neural networks, deep reinforcement learning, dimensionality reduction),
- Evolutionary algorithms (e.g., Divergent search, multi-objective optimization, Quality-Diversity optimization).
You will need strong analytical skills, programming background and experience with mechatronic systems.
Applicants are expected to have a First Class or Distinction Masters level degree, or equivalent, in a relevant scientific or technical discipline, such as computer science or mathematics. Applicants must be fluent in spoken and written English.
How to apply
To apply for this position, please follow the application guidelines.
In the application form, please write Dr Antoine Cully in the “Proposed Research Supervisor” field.
Early applications are encouraged. Informal inquiries about this position are also encouraged and can be directed to Dr Antoine Cully.
This position will be based at the South Kensington campus in central London.
Applicants are advised to visit our PhD page for general information on becoming a PhD student in the Department of Computing.
We are committed to equality and valuing diversity. We are also an Athena SWAN Silver Award winner, a Stonewall Diversity Champion, a Two Ticks Employer, and are working in partnership with GIRES to promote respect for trans people.