Research Associate on foundations for non-parametric probabilistic programming

Department of Computer Science, Parks Road, Oxford.

Research Associate on Better Languages for Statistics: foundations for non-parametric probabilistic programming

Fixed-term for 2 years

Grade 7: £32,817 - £40,322

• A full-time postdoctoral researcher post, fixed-term for 2 years, reporting to Sam Staton, is available to investigate the theory of probabilistic programming. 
• The appointee will work on one or more of the following topics: foundational issues for non-parametric programming languages, such as stochastic memoization; probabilistic representation theorems (such as generalized Aldous-Hoover or de Finetti theorems and their categorical setting); general purpose inference algorithms for non-parametrics; and applications of non-parametric probabilistic programming such as social science applications, program synthesis, or connections to deep net architectures. The exact scope of the research will depend on the skills and experience of the successful candidate.
• Candidates should have a PhD (or be very near completion) in computer science or mathematics, with a strong background in one or more of the following: probabilistic programming, theory of statistics, category theory, measure theory or programming language theory.
• The primary selection criteria include the abilities to conduct and complete research projects (as witnessed by peer-reviewed publications),
• We would particularly welcome applications from women and black and minority ethnic applicants who are currently under-represented within the Computer Science Department.

The closing date for applications is 12 noon on 17^th September 2020.

For further details and to apply please visit:
https://my.corehr.com/pls/uoxrecruit/erq_jobspec_details_form.jobspec?p_id=147321

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