2 postdoc positions in machine learning in Cambridge
We are seeking up to two highly creative and motivated Research Assistants/Associates to join the Machine Learning Group in the Department of Engineering, University of Cambridge, UK. The positions will involve research in direct collaboration with Professor Carl Edward Rasmussen.
The key responsibilities and duties of the roles are: conducting research in the fields of probabilistic machine learning, non-linear time series modelling (system identification) and reinforcement learning with applications to autonomous systems and control. Developing research objectives and proposals; presentations and publications; assisting with teaching and learning support; liaising and networking with colleagues and students; planning and organising research resources and workshops. The role will combine strong theoretical and analytical skills with programming experience.
Successful applicants will have or be near to completing a PhD in computer science, information engineering, statistics or a related area, and will have extensive research knowledge and experience in addition to a strong publication record in machine learning, including ideally papers in top machine learning conferences such as NIPS, UAI, ICML, and AISTATS. Excellent mathematical and programming skills are essential. Experience in two or more of the following areas: probabilistic modelling and scalable approximate inference (See: http://www.automaticstatistician.com/); probabilistic programming and bayesian nonparametrics research on an existing probabilistic programming language; MCMC methods; message passing and approximations of partition functions in regards to inference in graphical models will be necessary.
For more information and to apply see: http://www.jobs.cam.ac.uk/job/11220
