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School of Mathematical Sciences

PhD projects

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

Application deadlines:

19 March 2021 for the Higher Education Commission, Pakistan funded applications.

27 January 2021 for applications for the following funding sources:

Other funding bodies may have different deadlines. See fees and funding for details.

We welcome applications from self-funded students throughout the year.

Projects with guaranteed funding may be added throughout the year and will state the application deadline in the project listing.

PhD projects

Research groupProject TitleSupervisor
Algebra and Number Theory Automorphic forms: arithmetic and analytic interfaces [PDF 413KB]  Dr. Abhishek Saha
Combinatorics Discrete Voronoi Games [PDF 408KB]

Dr. Robert Johnson and Dr. Felix Fischer

Components in random combinatorial objects [PDF 516KB]

Dr. Dudley Stark

Complex Systems and Networks

Modelling stochastic processes in evolutionary games of resistance to cancer treatment [PDF 395KB]

Dr. Weini Huang and Dr. Dudley Stark 

Deadline: 9 April 2021 for July 2021 start

Full funding by EU Commission

Structure and dynamics of simplicial complexes [PDF 540KB] Prof. Ginestra Bianconi
Network modelling of spatial distributions from large data sets [PDF 433KB] Dr. Vincenzo Nicosia
Dynamical Systems and Statistical Physics

Random Walks in Restricted Domains and Standard Young Tableaux [PDF 422KB] Prof. Thomas Prellberg
Active anomalous stochastic search [PDF 538KB] Dr. Rainer Klages
Non-Markovian statistical mechanics: theory and applications [PDF 443KB] Dr. Rosemary Harris
Geometry and Analysis

Unique Continuation for Geometric Wave Equations, and Applications to Relativity, Holography and Controllability [PDF 642KB] Dr. Arick Shao
Quantum differential geometry and applications [PDF 408KB] Prof. Shahn Majid
The two-body problem in numerical and perturbative general relativity [PDF 439KB] Dr. Charalampos Markakis
Probability and Applications

Numerical Methods for High-Dimensional Problems in Finance [PDF 466KB] Dr. Kathrin Glau
Parametric Complexity Reduction in Finance [PDF 464KB] Dr. Kathrin Glau
Computational Methods for High-Dimensional Problems in Finance using PDE Methods and Deep Learning [PDF 427KB] Dr. Kathrin Glau
Potential Theory of Regenerative Compositions [PDF 404KB] Prof. Alexander Gnedin
Nonlinear expectation and risk-aware reinforcement learning [PDF 404KB] Prof. John Moriarty
Data Analytics of Large Coupled Structures [PDF 437KB]

Dr. Kathrin Glau and Dr. Wolfram Just

Full funding from QMUL mini-CDT Principal's Fund

Statistics and Data Science  Bayesian Uncertainty Quantification for Clustering Problems [PDF 408KB] Dr. William Yoo and Dr. Silvia Liverani
Robust extraction of dependence structures in high-dimensional nonlinear time series [PDF 530KB] Dr. Alex Shestopaloff 
Bayesian spatial modelling for health [PDF 401KB] Dr. Silvia Liverani


 

Enquiries and Further Information

For any general enquiries regarding the above PhD studentships please contact Dr Alex Fink, the Director of Postgraduate Research Studies, or Dr Weini Huang, the Deputy Director of Postgraduate Research 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 Preventive Medicine.