Senior Research Associate on FUN2MODEL: From FUNction-based TO MOdel-based automated probabilistic reasoning for DEep Learning

Department of Computer Science, Parks Road, Oxford.

Senior Research Associate on FUN2MODEL: From FUNction-based TO MOdel-based automated probabilistic reasoning for DEep Learning

Fixed term for 3 years, with the possibility of extension

Grade 8: Salary £41,526 – £49,553 p.a. (note: Grade 7: £32,817 - £40,322 p.a.)

The Automated Verification group at the Department of Computer Science has a vacancy for a Senior Research Associate on the ERC funded FUN2MODEL project.  Reporting to Professor Marta Kwiatkowska you will be a senior member of the FUN2MODEL project team and will be expected to provide overall leadership for the development of probabilistic verification and synthesis methods, including software implementation and PRISM extensions; to integrate techniques developed by other members of the team; and to liaise with Dave Parker to coordinate PRISM development.

You will also be responsible for carrying out research with an emphasis on data-centric modelling, coordination and reasoning for autonomous multi-agent systems, capturing cognitive and affective aspects. This includes causal reasoning based on Bayesian networks; game-theoretic methods and algorithmic schemes for coordination and collaboration; formalisation of provably robust and beneficial collaboration; extensions of PRISM modelling language and software; and relevant case studies.

You should hold a PhD (or close to completion) in computer science, mathematics or related discipline and have post qualification research experience, possess sufficient specialist knowledge of and demonstrable experience of: foundations of machine learning or statistics, probabilistic modelling/verification, and concurrency/multi-agent systems, and have experience of software development in relevant areas, such as verification and symbolic AI (SAT, SMT, etc), statistical inference or statistical model checking, numerical methods, constraint solving and optimisation. Knowledge of neural networks and Bayesian methods, and familiarity with human-robot interaction is highly desirable.

Whilst the role is a grade 8 position, we would be willing to consider candidates with potential but less experience who are seeking a development opportunity, for which an initial appointment would be at grade 7 (£32,817 - £40,322 p.a.) with the responsibilities adjusted accordingly; for Grade 7, you would be expected to hold a doctoral degree in Computer Science, mathematics, or related discipline (or be close to completion). This would be discussed with applicants at interview/appointment where appropriate.

The closing date for applications is 12 noon Wednesday 30th October 2019. Interviews are expected to be held week commencing 4 November 2019. For further details and to apply please visit: https://my.corehr.com/pls/uoxrecruit/erq_jobspec_details_form.jobspec?p_id=143187 

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