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Senior Research Associate on FUN2MODEL: From FUNction-based TO MOdel-based Automated Probabilistic Reasoning for DEep Learning

Applications for this vacancy closed on 4 March 2020 at 12:00PM
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
probabilistic reasoning and inference, including cognitive aspects. This may
include symbolic AI and verification/synthesis techniques; causal reasoning
based on Bayesian networks; planning and game-theoretic methods; and provably
safe and robust AI. Suitably qualified candidates will have an opportunity to
software implementation, liaising with Dave Parker to coordinate PRISM
codebase extensions.



You will be expected to regularly write research articles at a national level
for peer-reviewed 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: quantitative and/or probabilistic modelling, verification and
synthesis, concurrency/games/multi-agent systems, and symbolic methods, as
well as have proven 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 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 12.00 noon on Wednesday 4 March 2020.
Interviews are expected to be held week commencing 9 March 2020.



We would particularly welcome applications from women and black and minority
ethnic applicants who are currently under-represented within the Computer
Science Department.

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 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.

dc:spatial
Department of Computer Science, Wolfson Building, Parks Road, Oxford
Subject
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oo:formalOrganization
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vacancy:applicationClosingDate
2020-03-04 12:00:00+00:00
vacancy:applicationOpeningDate
2020-02-05 09:00:00+00:00
vacancy:furtherParticulars
vacancy:internalApplicationsOnly
False
vacancy:salary
type
comment

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 probabilistic ...

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
probabilistic ...
label
Senior Research Associate on FUN2MODEL: From FUNction-based TO MOdel-based Automated Probabilistic Reasoning for DEep Learning
notation
145222
based near
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