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EPSRC PhD Studentships in Mathematical Sciences – University of Reading

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  • PhD funding available

EPSRC PhD Studentships in Mathematical Sciences

The Department of Mathematics & Statistics at the University of Reading is pleased to offer up to two fully funded four year EPSRC PhD studentships in the Mathematical Sciences. Studentships are offered in a range of areas covering applied, numerical and pure mathematics and statistics. Further details on the available projects can be found below:

Project 1: Inference of nonlinear dynamics through data assimilation and machine learning

Project 2: Riemann-Hilbert problems and their applications in mathematical physics

Project 3: Numerical rare event analysis in multi-stable multi-scale systems

Project 4: Randomized parallel algorithms for data assimilation in numerical weather prediction

Project 5 - Large-scale least squares solvers with applications

Project 6 - Singular Integral Operators in Potential Theory: at the Analysis/Numerical Analysis Interface


Further details on the Department and its research groups can be found on the Department of Mathematics and Statistics website


Entry requirements

Applicants need to hold a first degree in mathematics, physics, statistics or a related relevant area and have obtained at least a 2.1 degree.



Studentships are open to UK and International applicants and are accompanied by a stipend of £15,609 per annum. Studentships will be available to commence in either September 2021 or January 2022.



Applications should be submitted via our online application system . Applicants do not need to provide a research proposal, but should indicate on their application form which project(s) they are interested in undertaking should their application be successful.

Applications will close on Friday 27th August 2021, with short-listed candidates being invited for interview shortly thereafter.

Applicants should be aware that the University is required to report diversity information to the umbrella funder, UK Research and Innovation (UKRI). UKRI receives this information as aggregated and anonymised data of recruitment rounds/cohorts, not as data about individual applicants. This data is collected so that UKRI has a better understanding of the students its training provision attracts and supports and is able to analyse general trends in student populations across UKRI.


Further information

Any queries should be directed to Mrs Kristine Aldridge (Postgraduate Research Administrator) -

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