Postdoctoral Research Associate/Assistant Positions in Machine Learning
THESE POSITIONS ARE NOW CLOSED
We are seeking up to three highly creative and motivated Postdoctoral Research Associates/Assistants to join the Machine Learning Group in the Department of Engineering, University of Cambridge, UK.
Post 1: Building an Automated Statistician. This postdoc will be working with Zoubin Ghahramani in collaboration with Google, and should have extensive experience in Bayesian model comparison and scalable approximate inference.
Post 2: Probabilistic Programming and Bayesian Nonparametrics. This postdoc will be working with Zoubin Ghahramani in collaboration with MIT and Oxford and should have research experience in these two areas.
Post 3: Machine Learning for Autonomous Systems and Control. This postdoc will be working jointly with the Control Group at Cambridge, in a team including Carl Rasmussen, Jan Maciejowski, and Zoubin Ghahramani. This project will focus on bridging Bayesian inference for machine learning, reinforcement learning methods, and Model Predictive Control methods for autonomous and intelligent systems.
The successful applicants will have or be near completing a PhD in computer science, engineering, statistics or a related area, and will have extensive research experience and a strong publication record in statistics, probability, machine learning and/or control theory. Preference will be given to applicants with some experience in large-scale modelling with Bayesian methods, non-parametric Bayesian models, approximate inference and experience with reinforcement learning or control.
To apply complete form CHRIS/6 (http://www.admin.cam.ac.uk/offices/hr/forms/chris6/) and send with your CV which should include a list of your publications and names of at least two referees, and a covering letter indicating which posts you wish to be considered for, in pdf format by email to Diane Hazell (firstname.lastname@example.org).
Applications should be sent so as to reach us not later than 25 November 2013.
Quote Reference: NM01955 (Posts 1 and 2), or NM01954 (Post 3).