The Role
We have an exciting opportunity for an internship within our AI & Algorithms department, focused on robotics and robot learning. This is a paid placement of between 6 and 12 months' duration with a flexible start date, and is suitable for final-year PhD students looking for industry experience, with the hope to transition into an industry role after graduation.
As a Robotics & Robot Learning Engineer (PhD Intern), you'll get involved with a range of diverse projects, working with and supported by a talented team of experts and mentors. You'll engage in hands-on tasks spanning the full pipeline of a robotic learning system — from data collection and model training through to deployment on real hardware. With cutting-edge labs, robotic platforms and computing resources at your disposal, you'll use technology to solve real-world problems across healthcare and industrial applications.
What you’ll be doing
- Working alongside our engineers to build and deploy robot learning systems, from data collection (teleoperation, sensor logging, simulation) through to training, testing, and real-world deployment.
- Getting hands-on with robotic hardware and software integration — helping robots perceive, learn from data, and act reliably in the real world.
- Supporting client projects that apply robotics and AI to solve real-world problems in healthcare and industrial settings.
- Learning software and systems engineering skills in mixed-discipline teams, attending stand-ups and contributing to planning sessions.
- Contributing to our internal research and development programs, building on state-of-the-art robotics and AI literature to produce market-leading solutions and compelling demonstrations that showcase our expertise to clients.
- Communicating the results of your work to colleagues and clients.
What you can bring
We are looking for a final-year PhD student in robotics, computer science, AI/machine learning, or a related computational discipline.
What matters most is that you understand the complexity of a robotic system, and have hands-on experience across the full pipeline, from data collection through to real-world deployment.
You will also have:
- One or more publications in a leading journal or conference relevant to the sector (e.g. in T-RO, ICRA, IROS, ICML, CoRL, RSS, or NeurIPS)
- Practical, hands-on experience collecting data from and/or deploying software or models onto a physical robotic system (e.g. teleoperation, sensor integration, hardware-in-the-loop testing, sim-to-real transfer).
- Strong programming skills (Python and/or C++), comfortable writing and maintaining real software rather than one-off scripts, with an understanding of modern version control (e.g. Git).
- Understanding of mechatronic system (actuators, sensing, etc)
- A clear interest in applying your research to real-world robotics problems, and in making the transition from academia into an industry engineering role.
While not essential requirements, we would also be very interested if you have experience with any of the following:
- ROS or other robotics middleware
- Computer vision (SfM, SLAM, VLM)
- Reinforcement learning or imitation learning
- Transformer, diffusion, VLA, WAM models
- Sensor integration (cameras, force/torque sensors, LiDAR, IMUs)
- Simulation environments (e.g. Isaac Sim, MuJoCo, Gazebo)
- Edge compute and embedded deployment
- Bayesian statistics or signal processing
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