- Science and Research
- United Kingdom - Dyson Robot Learning Lab - London
At Dyson, our goal is to build a world-leading robotics team focused on developing advanced domestic robots to go into real homes and help real people. Our multidisciplinary team is already one of the largest home Robotics groups in the world and is growing fast. We offer applicants the opportunity to work on some of the field's most challenging problems alongside some of its best engineers and scientists.
We’ve been developing robot technology for over 20 years, but this is just the start. In an effort to help build the next generation of advanced domestic robots, we have opened a new Dyson Robot Learning Research Lab in the heart of London, as well as creating the largest robotics centre in the UK at Hullavington Airfield, one of Dyson’s research and innovation hubs in Wiltshire.
The Dyson Robot Learning Lab (DysonRL) in London is looking to grow a team of research scientists and research engineers working to put functional advanced robotic solutions into the homes of the general public. We are looking for people to help us investigate robust solutions to diverse real-world problems in machine perception, action, and intelligence. Successful candidates will be working in a supportive environment within a team of experts that is constantly aiming to improve itself and the world of robotics.
About the role
Research Scientists at the Dyson Robot Learning Lab (DysonRL) lead development of novel robot learning methods with the goal of solving real world problems with domestic robotics. Our research scientists work at the forefront of a variety of disciplines, including reinforcement learning, imitation learning, robot perception, control, simulation-to-reality transfer, unsupervised representation learning, and other broader deep learning areas.
Key responsibilities include:
Drive the field forward by designing, implementing and evaluating novel robot learning methods to solve grand challenges within the home.
Identify opportunities to apply robot learning techniques to other robotics teams within Dyson.
Work with research engineers to rapidly prototype new methods.
Report and present research verbally and in writing, both internally and externally.
Keep up to date with the state-of-the-art in the field of robot learning, with particular focus on robot manipulation.
Communicate with external collaborators and maintain relationships with relevant research labs.
We require the following skills and experience:
PhD (or equivalent industrial research experience) in a robot learning discipline.
Have made significant contributions to the field of robot learning, e.g., through publications at CoRL, ICRA, RSS, ICML, ICLR, NeurIPS, CVPR, IROS, etc.
Strong knowledge and experience of applying reinforcement learning, imitation learning, and robot vision algorithms to simulation and/or real robot manipulation platforms.
Strong knowledge and experience with modern machine learning frameworks (PyTorch, Tensorflow, Chainer).
It would be advantageous to have the following skills and experience:
Experience in applying deep learning to real world robot platforms.
Experience in large-scale training.
Experience with Ubuntu / Linux.
Good Knowledge of Robotics.
Fair Experience with ROS and Docker.
A passion for advanced domesticated robots.
• Performance related bonus
• Company paid Life Assurance
• Discounts on Dyson machines
• Competitive pension scheme
• Season ticket loan for train travel
• Purchase additional holidays
• 27 days holiday plus statutory bank holidays
• Digital lifestyle Assist
• Electric vehicle scheme
• Private Medical insurance for all employees
• Employee Assistance Program for employee and dependents
• Digital GP and prescription service
• Fertility treatment support
Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.