Department of Mathematics and Statistics

We are currently offering two fully funded, four year PhD scholarships in all areas of the mathematical sciences (including statistics). These scholarships are in the EPSRC framework for 'National Productivity Investment Fund 2018 training grant', and thus, candidates must be a UK citizen, or a EU citizen fulfilling the EPSRC requirements.

Deadline for entries is 30th June 2018.

The starting date of the scholarships is the 1st of October, 2018.

The selection process will be as follows:

Please, send a cover letter (including research interests), a detailed CV (including transcripts), and two reference letters, by email, to Dr. Gabriel Barrenechea.

After a ranking process (and possible interviews), two candidates will be chosen.

These candidates will be given a number of projects to choose from, ranging over all the areas of applied mathematical sciences.

The deadline for applications is the 30th of June, 2018, and the results are expected to be communicated on the 15th of July.

For any inquiries, please contact Dr. Gabriel Barrenechea, or Dr. Michael Grinfeld.

The Department of Mathematics & Statistics is one of the largest of its kind in Scotland, with an international reputation in the use of mathematical analysis for real-world problems.

Research is focused on applied mathematics and statistics in the broadest sense, with an emphasis on modelling and analysis of real-world problems. The Department has collaborative links with researchers in many institutions, including other universities, research establishments and industry in the UK, Europe, the USA and elsewhere in the world.

Research activities are focused in five interdependent groups:

• Applied Analysis
• Continuum mechanics and industrial mathematics
• Numerical analysis and scientific computing
• Population modelling and epidemiology
• Stochastic analysis

Applied Analysis

In many areas of scientific and industrial research, the mathematical modelling of physical and biological processes leads to complicated sets of differential equations and large networks of interrelated components. Understanding how to analyse these networks and sets of equations is key to gaining insight into the real-life systems they are modelling.

Continuum mechanics and industrial mathematics

Research focuses on both the development of accurate mathematical theories of physical materials and the use of these theories in the mathematical modelling of industrial processes – from the flow of liquid to how ultrasound waves travel through structures.

Numerical analysis and scientific computing

Research activity is concentrated on the construction and analysis of methods for numerical solutions of nonlinear differential equations, the computational solution of problems of practical interest and several aspects of numerical linear algebra.

Population modelling and epidemiology

The overarching theme of the group is the use of modelling techniques to extract information from complex data sets with an emphasis on practical problems on the epidemiology of infectious diseases, ecological complexity, marine and fisheries modelling and mathematical cell biology.

Stochastic analysis

Research into theoretical and methodological problems of various types of stochastic processes in space and time. Study of real-life situations across a wide range of application areas which demonstrate a degree of randomness – from molecules bouncing off each other to fluctuations in the stock market.