[TYPES/announce] PhD studentship on "Probabilistic Property-Based Testing" at the University of Edinburgh

[James Cheney]

We are now accepting applications for 3-year PhD studentship on a project
called "Probabilistic property-based testing" in the School of Informatics,
University of Edinburgh.

http://homepages.inf.ed.ac.uk/jcheney/group/ppbt.html

The aim of the project is to explore the hypothesis that property-based
testing (e.g. QuickCheck) is a form of probabilistic programming.
Property-based testing is a widely used and powerful form of lightweight
randomized testing, but it has been developed largely independently of
increasingly sophisticated probabilistic programming languages and
inference algorithms.  This project will study the consequences of adopting
the perspective that property-based testing is a form of probabilistic
programming, and investigate subproblems such as inducing good properties
from programs or test data; testing complex programs using advanced
sampling techniques that provide error bounds; and synthesizing suitable
data generators or automatically providing concise explanations why a
property fails to hold.

Possible application areas include randomized testing of programming
language designs and type systems themselves (following e.g. PLT Redex or
logic programming-based approaches to language specification), as well as
traditional system specification and testing problems.

The studentship is tenable for 3 years, for a student of any nationality,
and includes a stipend of £14,777 per year (tax free and increasing with
inflation), supported by Huawei. The School is also partnered with data
science and AI centres of excellence such as The Alan Turing Institute in
London and the Bayes center in Edinburgh, and there will be ample
opportunities to engage with these institutes, via workshops and other
schemes.

The ideal candidate would have a strong background in functional or logic
programming (e.g. Haskell, OCaml, Erlang, Prolog), or a strong background
in machine learning. Candidates already familiar with probabilistic
programming or symbolic machine learning (e.g. relational learning,
probabilistic logic programming) are especially welcome.

Applications from prospective students interested in starting a PhD in the
next academic year should be submitted by March 18, 2019 at the latest.
Applications received by January 31, 2019 will receive full consideration;
after that date applications will be considered until the position is
filled.  The anticipated start date is September 2019 but earlier start
dates may be possible.

To apply, please submit an application to the 3-year CISA PhD programme:

https://www.star.euclid.ed.ac.uk/public/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=PRPHDINFMT9F&code2=0122

Further instructions and information about PhD study at CISA and the
University of Edinburgh is available here:

http://web.inf.ed.ac.uk/cisa/study-with-us
https://www.ed.ac.uk/informatics/postgraduate/apply

For more information please contact Vaishak Belle (vaishak at ed.ac.uk) and/or
James Cheney (jcheney at inf.ed.ac.uk).
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