Open positions

Are you passionate about Legged Robotics, Optimization and AI? Interested in joining a young lab and conducting cutting-edge research? Then, you must consider to apply for one of our open positions.

PhD students

We are continuously looking for OUTSTANDING applicants that wish to pursue their PhD studies on the following topics:

  • Model predictive control in legged robotics
  • Numerical optimization and optimal control
  • Reinforcement learning for robot control
  • Symmetries, group theory and contact physics for robotics

We expect that outstanding candidates have significant experience or papers in relevant fields such as: legged locomotion and robotics, numerical optimization, robot learning, model predictive control, state estimation and perception, etc. Applicants are expected to have a good level of programming skills in C++, Python and ROS, and to be willing to work in team.

We currently have a fully-funded PhD position to be filled as soon as possible. We also have several PhD positions through the exciting EPSRC Centre for Doctoral Training in Dependant and Deployable AI for Robotics (D2AIR) and EPSRC and MOD Centre for Doctoral Training in Sensing, Processing, and AI for Defence and Security (SPADS). Before applying discuss the project proposal with Carlos Mastalli and include a complete CV (including publications if they are), motivation letter, and the contact information of two references. During the application, mention that you would like to work with Carlos Mastalli and within the Robot Motor Intelligence (RoMI) Lab.


We are excited to welcome motivated research scientist with a rich diversity in backgrounds and experiences (if funding allows). We are particularly interested in scientist that have depth knowledge in:

  • Numerical optimization
  • Machine learning
  • Robot design

and have applied them in robotics, control, and computer vision.

Currently, we have funding for one postdoc position on contact-implicit loco-manipulation. In this position, you will play a pivotal role in pioneering the next generation of contact-implicit motion generation approaches for loco-manipulation in legged robots. Your responsibilities will include enhancing loco-manipulation skills in quadruped robots, creating high-quality open-source software, and pushing the boundaries of robotic capabilities. We are seeking candidates with an outstanding research track record in at least one of the following areas:

  1. numerical optimization for robotics,
  2. contact physics,
  3. optimal control and model predictive control (MPC), and
  4. deep reinforcement learning (RL).

You must hold a PhD/DPhil in robotics, computer science, machine learning, informatics, AI, or a closely related field, or be close to completion. Practical experience with real robots and excellent teamwork skills are essential. We welcome applicants from both legged locomotion and manipulation backgrounds, and the ideal starting date for this position is February/March 2024.

Please include a complete CV, a research statement describing you previous research and future goals, a complete list of publications, copies up to three selected papers and references.

Futhermore, you could take a look at the following funding schemes: UKRI Future Leaders Fellowships, Marie-curie fellowship, and Royal Academy of Engineering Fellowship, and Newton International Fellowships. We also support applicants that are keen to apply for postdoctoral fellowships.