Research Associate on Probabilistic and Differentiable Programming
Posted: 27th February 2020
Department of Computer Science, Parks Road, Oxford.
Postdoctoral Researcher in Probabilistic and Differentiable Programming
Fixed-term for 2 years, extendable to three
Grade 7 £32,236 - £39,609 p.a.
A full-time postdoctoral researcher post, fixed-term for 2 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 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.
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.
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.
The closing date for applications is 12.00 noon on 14th April 2020.
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