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

Computer Science

University of Oxford, Oxford, UK

Overview

  • Posted on: 12th Feb 2021
  • Salary: Grade 8: Salary £41,526 - £49,553 p.a.
  • REF: 149540
  • Closes: 12th March 2021
  • Contract Type: Fixed-Term/Contract
  • Hours: Full Time

Job Details

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

Department of Computer Science, Parks Road, Oxford

Grade 8: Salary £41,526 – £49,553 p.a.

Full Time and Fixed Term for 36 months, with the possibility for an extension. To start as soon as possible (no later than 1st October 2021)

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

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.

We are looking for a motivated Senior Research Associate to play a key role in the ERC funded FUN2MODEL project.
You will be a senior member of the collaborative project team, reporting directly to Professor Marta Kwiatkowska, and you will provide leadership for the development of theories, models and algorithms for quantitative/probabilistic verification and synthesis to enable robust AI. Based within an internationally leading research group, you will benefit from working in Oxford University’s acclaimed Computer Science Department, located in the heart of Oxford’s Scientific Keble Triangle.

You will be responsible for carrying out research with an emphasis on automated verification and synthesis, applied to machine learning. This may include neuro-symbolic approaches; program synthesis; symbolic methods; probabilistic verification; statistical relational AI; robustness and certification. Suitably qualified candidates will have an opportunity for software implementation, liaising with Dave Parker to coordinate PRISM codebase extensions. The exact scope of the research will depend on the skills and experience of the successful candidate.

You will be expected to regularly write research articles for leading peer-reviewed conferences and journals, agree clear task objectives, organise and delegate work to other members of the team, and share responsibility for shaping the research group’s plans.
You should hold a PhD (or close to completion) in computer science, mathematics or related discipline and have post qualification research experience, possess specialist knowledge and demonstrable experience across some/all of: program/strategy synthesis; symbolic/neuro-symbolic methods; probabilistic/statistical verification; and Bayesian learning, as well as proven experience of software development in relevant areas.

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 12th March 2021. Interviews are expected to be held week commencing 29th March 2021.

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.

Contact Person :

HR Officer

Vacancy ID :

149540

Contact Phone :

Closing Date & Time :

12-Mar-2021 12:00

Contact Email :

hr@cs.ox.ac.uk

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Senior Research Associate on FUN2MODEL

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