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Research Associate on Probabilistic and Differentiable Programming

Applications for this vacancy closed on 6 November 2020 at 12:00PM
<div xmlns="http://www.w3.org/1999/xhtml"> <p></p><p>Department of Computer Science, Parks Road, Oxford.</p><br> <p>Title: Postdoctoral Researcher in Probabilistic and Differentiable Programming Status (fixed-term)</p><br> <p>Grade &amp; salary: Grade 7 &#163;32,817 - &#163;40,322 p.a.</p><br> <p>A full-time postdoctoral researcher posts for two years (with the possibility of extension), reporting to Professor Luke Ong, is available to investigate topics in probabilistic and differentiable programming.</p><br> <p>The appointee will work on one or more of the following topics: automatic analysis of (positive) almost-sure termination of classes of differentiable, statistical programs using martingales; verification and static analysis of correctness and convergence properties of inference algorithms (including variational inference) using a variety of formal methods; notions of differentiability of densities of (higher-order, recursive) statistical programs, and semantics and pragmatics of deep statistical programming languages; automatic compilation to densities, disintegration algorithms, and symbolic Bayesian inference. The exact scope of the research will depend on the skills and experience of the successful candidate.</p><br> <p>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 and differentiable programming, statistical machine learning, Bayesian deep learning, semantics of programming languages, lambda calculus and types, category theory, probability and measure theory. Experience of actively collaborating in the development of research articles for publication is highly desirable.</p><br> <p>The primary selection criteria include the abilities to conduct and complete research projects (as witnessed by peer-reviewed publications), and contribute ideas for new research projects; and writing skills.</p><br> <p>The closing date for applications is 12 noon on 6 November 2020.</p><br> <p>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.</p> </div>
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Department of Computer Science, Parks Road, Oxford.
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vacancy:applicationClosingDate
2020-11-06 12:00:00+00:00
vacancy:applicationOpeningDate
2020-10-08 09:00:00+01:00
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False
vacancy:salary
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Department of Computer Science, Parks Road, Oxford.


Title: Postdoctoral Researcher in Probabilistic and Differentiable Programming Status (fixed-term)


Grade & salary: Grade 7 £32,817 - £40,322 p.a.


A full-time postdoctoral researcher posts for two years (with the possibility of extension), reporting to Professor Luke Ong, is available to investigate topics in probabilistic and differentiable programming.


The appointee will work on one or more of the following topics: automatic analysis of (positive) almost-sure termination of classes of differentiable, statistical programs using martingales; verification and static analysis of correctness and convergence properties of inference algorithms (including variational inference) using a variety of formal ...

Department of Computer Science, Parks Road, Oxford.



Title: Postdoctoral Researcher in Probabilistic and Differentiable Programming
Status (fixed-term)



Grade & salary: Grade 7 £32,817 - £40,322 p.a.



A full-time postdoctoral researcher posts for two years (with the possibility
of extension), reporting to Professor Luke Ong, is available to investigate
topics in probabilistic and differentiable programming.



The appointee will work on one or more of the following topics: automatic
analysis of (positive) almost-sure termination of classes of differentiable,
statistical programs using martingales; verification and static analysis of
correctness and convergence properties of inference algorithms (including
variational inference) using a variety of formal ...
label
Research Associate on Probabilistic and Differentiable Programming
notation
147962
based near
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