Research Fellow/Senior Research Fellow position in Machine Learning for Robotics
We are looking for a (Senior) Research Fellow at the intersection of robotics and machine learning.
Autonomous robots will play an increasingly important role in the future, e.g., in the context of healthcare, space exploration, or supporting humans in day-to-day activities. Key challenges, autonomous robots face are that they need to be able to learn from data and adapt fast to new situations without strong human interventions. Currently, autonomous learning systems either require vast amounts of data or they require human guidance. This project centers around approaches for data-efficient autonomous learning for robotics, e.g., by means of probabilistic modeling, transfer learning or using generic priors that constrain the learning system.
The Statistical Machine Learning Group is part of the Centre for Artificial Intelligence at UCL and has a strong background in probabilistic modelling, data-efficient machine learning, and reinforcement learning.
The successful applicant will lead and contribute to research projects at the intersection of statistical machine learning and climate science. They are also expected to contribute to student supervision and interact with research and project partners. The key objective is to design and evaluate machine learning approaches to advance the current state of the art in robot learning.
The post is graded as Grade 7 or Grade 8, with starting salary in the range £35,965 to £43,470 (Grade 7) or £44,674 to £52,701 (Grade 8) per annum (including London Allowance). Progression through the salary scale is incremental.
The funding for this post is for 24 months in the first instance.
The successful applicant will have a PhD (or close to be obtaining a PhD) in machine learning, statistics, computer science, robotics or a relevant area. They should have a track record of internationally recognized research and be able to work as part of a team. Research skills (theoretical and empirical, planning and documentary) plus effective written and verbal communication skills are essential