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Research Associate in Bayesian deep learning / Reinforcement learning

Posted: 2nd October 2018

Department of Computer Science, Wolfson Building, Parks Road, Oxford.

Research Associate in Bayesian deep learning / Reinforcement learning

Fixed-term for up to 24 months

Grade 7: £32,236 - £39,609 p.a.

The Artificial Intelligence and Machine Learning group at the Department of Computer Science has a new opening for a Research Associate in Bayesian deep learning / Reinforcement learning, working together with Professors Yarin Gal and Shimon Whiteson, in an industrial partnership with Accenture.

You will develop fundamental tools at the intersection of reinforcement learning and Bayesian deep learning, in the context of real-world problems, and involving both theoretical work, conducting original research in these fields, as well as extensive empirical analysis on challenging tasks.

The primary selection criteria are a doctoral degree (or close to completion) in Computer Science or related discipline, together with related experience, a documented track record of the ability to conduct and complete research projects, as witnessed by published peer-reviewed work in machine learning (or a related area), and strong mathematical skills in probability and statistics.  Good knowledge of the current state-of-the-art in reinforcement learning and Bayesian deep learning, and experience supervising PhD students and managing projects is highly desirable.

The closing date for applications is 12 noon on 12th November 2018.

Our staff and students come from all over the world and we proudly promote a friendly and inclusive culture. Diversity is positively encouraged, through diversity groups and champions, for example http://www.cs.ox.ac.uk/aboutus/women-cs-oxford/index.html, as well as a number of family-friendly policies, such as the right to apply for flexible working and support for staff returning from periods of extended absence, for example maternity leave.

For further details and to apply please visit:

https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.jobspec?p_id=137298