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PhD Studentships in Probabilistic Artificial Intelligence

University of Warwick

Qualification Type: PhD
Location: Warwick
Funding for: UK Students, EU Students, International Students
Funding amount: PhD fees covered + annual stipend at the EPSRC rate (£19,237 for academic year 24/25)
Hours: Full Time
Placed On: 19th February 2024
Expires: 30th April 2024

Applications are invited for two PhD positions in “Probabilistic Artificial Intelligence” at the Department of Statistics, University of Warwick. The successful applicants will be part of the ProbAI project, a £9m UKRI-funded project with hubs in Warwick, Bristol, Cambridge, Edinburgh, Lancaster and Manchester. Probabilistic Artificial Intelligence involves the embedding of probability models, probabilistic reasoning and measures of uncertainty within AI methods. The ProbAI hub will develop a world leading, diverse and UK-wide research programme in probabilistic AI, that will develop the next generation of mathematically-rigorous, scalable and uncertainty-aware AI algorithms.

These studentships will be based at the University of Warwick Statistics Department. Within the Statistics department there is wide expertise in probability, computational statistics, and Bayesian statistics (amongst others). There are also broader interests covering many related areas in the neighbouring Depts of Mathematics and Computer Science.

Applicants should have an interest in Machine Learning or Artificial Intelligence interpreted widely, and applicants with more theoretical, more applied and/or more computational interests are equally encouraged to apply. A background in machine learning is helpful but more value is placed on a rigorous mathematical and statistical education.

Successful applicants will have PhD fees covered as well as receiving an annual stipend at the EPSRC rate (£19,237 for academic year 24/25) and a generous Research Training and Support fund to cover research equipment and travel costs. Studentships will be for up to 4 years. Successful applicants will have the opportunity to join the Warwick Centre for Doctoral Training in Mathematics and Statistics (https://warwick.ac.uk/fac/sci/statistics/postgrad/research/).

How to apply

Applicants should apply directly to the Warwick PhD admissions portal and quote ProbAI in the application (in the personal statement and in the source of funding). If you are potentially interested in other PhD opportunities in Warwick Statistics, you can also indicate that in your personal statement and/or source of funding. All general information can be found at https://warwick.ac.uk/study/postgraduate/apply/research.

To be considered for these ProbAI positions, you are advised to apply as soon as possible and before 30th April 2024. Applications will be regularly reviewed and may be filled well in advance of this date. After this date, applicants are still welcome to apply but positions may have already been filled. 

In your personal statement please include information about your motivation and suitability for the ProbAI project. Precise information about an area you wish to work in is not necessary, although an indication about your research interests would be very helpful.

Please ensure that your referees are aware that they will need to upload their supporting statements by the deadline for these positions as decisions will be made soon after this deadline.

Competitive applications are likely to require strong Undergraduate and Masters achievement, typically at first class and distinction levels respectively for UK applicants, and will most likely have completed degrees in Statistics, Mathematics, Data Science, Computer Science, although we are open to consider more unusual routes from motivated applicants.

Informal enquiries are strongly encouraged (to Gareth Roberts, Gareth.o.roberts@warwick.ac.uk, Paul Jenkins, P.Jenkins@warwick.ac.uk, or Matthew Thorpe, matthew.thorpe@warwick.ac.uk). We'd be very pleased to hear from you and would be happy to advise about your application during a brief informal video call if that would be helpful.

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