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School of Mathematical Sciences

PhD projects

The School of Mathematical Sciences invites applications for the PhD projects listed below.

Application deadlines:

Application deadlines for funded projects are listed in the tables below, but please be aware that applications will be considered on a rolling basis.

Unfunded projects are listed without application or start deadlines, and we welcome applications from self-funded students throughout the year.


Combinatorics, Algebra & Number Theory


Project Start date Application deadline
Zeros of Graph Polynomials and Computational Phase transitions
Supervisor: Viresh Patel
Chern classes of tropical manifolds
Supervisor: Felipe Rincón


Data Science, Statistics & Probability

Project Start date Application deadline
New frontiers in extreme data analysis
Supervisor: Eftychia Solea
Funding: QMUL 
Sep 24 31 May 24
Novel causal models for multivariate functional data
Supervisor: Eftychia Solea
Funding: QMUL
Sep 24 31 May 24
Bayesian Spatio-temporal Modelling for Biodiversity
Supervisor: Silvia Liverani
Bayesian Analysis of Multiple Count Time Series
Supervisor: Matteo Iacopini
Universality in Topological Data Analysis
Supervisor: Omer Bobrowski & Primoz Skraba
Data-driven Image Processing Methods with Applications to Wildlife Conservation
Supervisor: Kostas Papafitsoros
Applications of Universality in Topological Data Analysis
Supervisor: Omer Bobrowski

Geometry, Analysis & Gravitation

Project Start date Application deadline
Regularity theory and singularity analysis of geometric PDEs via phase field approximations
Supervisor: Shengwen Wang
Funding: QMUL
Sep 24 31 May 24
De Sitter matrix models and field theory
Supervisor: Tarek Anous
Funding: QMUL Research Support Fund
Sep 24 31 May 24
Search for Dark Matter with Gravitational-wave Detectors
Supervisor: Hong Qi
Innovative methods for gravitational wave parameter estimation
Supervisor: Hong Qi
Numerical relativity for fundamental physics
Supervisor: Katy Clough
p-evolution equations with low-regular coefficients
Supervisor: Claudia Garetto
Gravitational waves in higher derivative theories of gravity
Supervisor: Pau Figueras
From computational fluid dynamics to gravitational wave observations
Supervisor: Charalampos Markakis
Gravitational wave science with the LISA and LIGO
Supervisor: Charalampos Markakis

Enquiries and Further Information

For any general enquiries regarding the above PhD studentships please contact Dr Reem Yassawi, the Director of Graduate Studies, or Dr Alex Shestopaloff, the Deputy Director of Graduate Studies. For more administrative queries about the PhD programme at Queen Mary, please contact Katie Hale, the PGR Programmes Officer.

If you have already secured funding for your PhD studies and therefore do not wish your application to be considered within the studentship competition please state this on the appropriate part of your application form.

Choosing your Research Topic

It is highly recommended that first you make up your mind in which area of mathematics you wish to work and, ideally, to even think of prospective PhD supervisors at our School. It is important that your supervisor shares your research interests such that he/she can successfully guide you in your research. Many PhD students in mathematics do not pursue targeted research projects specified at the outset. Instead, they develop an agreed programme of study in discussion with their supervisor during their first year here. This programme tends to evolve in response to what has been learned during preliminary studies.

With this in mind, the important question for a prospective student is: Are my interests aligned with those of the School? The following links provide information on the general research strengths of the School:

Collaborative Research 

From time to time, we have projects available which are co-sponsored by an industrial partner, or which are run jointly with colleagues in another department at Queen Mary. Recent examples of the latter include the School of Biological and Chemical Sciences, the School of Electronic Engineering and Computer Science, and the Wolfson Institute of Population Health.

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