Senior Model Based Reinforcement Learning Scientist

current vacancies

Senior Model Based Reinforcement Learning Scientist

We are looking to hire exceptional scientists that join our model based reinforcement learning team. You will be contributing to our research work and developing algorithms that are both theoretically rigorous, yet scalable to domains approaching real-world complexity (e.g., to Robot Operating System, MuJoCo/Roboschool).

Your responsibilities

  • Develop novel model-based reinforcement learning algorithms for robotic problems
  • Design and conduct large-scale experiments using ROS or MuJoCo/Roboschool
  • Conduct theoretical analysis of proposed algorithmic solutions
  • Contribute to research work and publications the team is working on
  • Develop and run large-scale experiments to identify effective solutions
  • Work closely with other researchers and engineers in an Agile team

Skills and experience

  • PhD in Computer Science, Electrical Engineering, or an equivalent degree in a related field
  • Strong background in the fields of reinforcement learning, robotics, and/or control theory
  • Strong knowledge of machine learning and artificial intelligence algorithms
  • Background in the fields of optimisation, probability theory, and statistical learning is a big plus
  • Publication thread in A-level machine learning and robotics conferences, including but not limited to ICML, NIPS, AISTATS, UAI, AAAI, ICRA, RSS, IROS
  • Publication in high-impact machine learning and robotics journals, including but not limited to JMLR, PAMI, JAIR, IJRR, RA-L, RAS
  • Knowledge of C++ and ROS
  • Knowledge of Python frameworks for automatic differentiation/optimisation (e.g., TensorFlow, PyTorch, Chainer) is a big plus
  • Familiarity with MuJoCo/Roboschool or OpenAI gym is a big plus

What we offer

Competitive package to match experience consisting of salary and employee stock options, an energetic and fun start-up environment, opportunities for professional development, a team of exceptionally talented colleagues, a position to shape the future of AI.


Cambridge, United Kingdom.

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