Postdoctoral Research Assistant in Statistical Machine Learning

Updated: 6 days ago
Location: Oxford, ENGLAND
Deadline: 18 Aug 2017

Applications are invited for a full-time postdoctoral research assistant in statistical machine learning, to work on Bayesian nonparametric methods for recommender systems, partially funded by an EPSRC Grant awarded to François Caron and an ERC project led by Yee Whye Teh.

The objective of this project is to investigate static and dynamic Bayesian non-parametric models which can capture power-law behaviour as well as additional interpretable structure in relational data, and to develop scalable recommender system algorithms based on these models. The main duties and responsibilities of the postholder will include conducting original research, developing new modelling and complex methodologies for large and complex nonparametric models, develop theoretical and empirical frameworks for analysing behaviour of developed methodologies, publish outcomes of research and disseminate research findings in talks at suitable seminars, workshops and conferences.

Applicants are sought who already have, or are close to the completion of, a doctorate in statistics, machine learning, computer science or affiliated discipline.

The successful candidate will have significant relevant experience in Bayesian statistics, the ability to conduct and complete high quality research independently, collaborate effectively with PIs and project partners, communicate results effectively and be able to supervise the research of DPhil students or junior researchers attached to the project.

Queries about the post should be addressed to Professor François Caron: or Professor Judith Rousseau: .

The closing date for applications is 12.00 noon on Friday 18 August 2017. Interviews will be held on Friday 8 September 2017.

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