PhD Studentship in Stochastic Analysis of Biological Systems

"Biology is the new physics" -- Philip Hunter

Recent advances in technology have massively improved our ability to conduct experiments and collect data giving new insights into biological systems. The classical approach to mathematical biology has been to use analytic tools, e.g., ordinary/partial differential equations, perturbation theory etc. In this project, we will develop stochastic models and study how they are related to their deterministic counterparts. Specific examples include models from (i) epidemiology such as epidemic processes on (random) graphs, (ii) stochastic reaction networks and systems biology such as enzyme kinetic and autocatalytic reactions, (iii) ecology such as Lotka—Volterra systems. We will start with simple Markovian models and then extend them to more general non-Markovian ones.

The goal of the project is twofold: On the theoretical side, we will investigate limiting behaviour of the stochastic systems, e.g., (functional) laws large numbers, (functional) central limit theorems, large deviations principles, stationary distributions. On the computational side, we will develop efficient simulation algorithms and statistical methodology for parameter inference.

The project will require both theoretical (probability theory, functional analysis) and computational skills (programming in Julia/R/Python/C/C++).

Specific projects in the following broad areas of mathematics;

• Applied Probability
• Stochastic Processes
• Epidemic Modelling
• Mathematical Biology
• Stochastic Reaction Networks

can be found by visiting www.maths.nottingham.ac.uk/app/projects and then searching for the keywords “Wasiur” or “KhudaBukhsh”.

Funding

Funding covers a stipend at the RCUK rate (£17,668 for 2022-23) and fees at the level of a UK domestic student.

For further information about postgraduate study in mathematics, please see:

www.nottingham.ac.uk/pgstudy/course/research/mathematics-phd

www.nottingham.ac.uk/mathematics/study/research/index.aspx

Entry requirements

Applicants are normally expected to have a 2:1 Bachelor or Masters degree or international equivalent, in a related discipline. Any offer will be subject to the University admissions requirements. Applicants must be resident in the UK and have a 1st class Mathematics degree, preferably at the level of an MSc/MMATH, or international equivalent. Graduates of another quantitative discipline (e.g. Physics, Data Science, Engineering, Astronomy) may also be considered if they have a strong interest in the project.

Application Process

Applications to be made via the central University of Nottingham admission process (NottinghamHub, www.nottingham.ac.uk/pgstudy/how-to-apply/how-to-apply.aspx).

Please send any enquiries to Dr. Wasiur KhudaBukhsh (Wasiur.KhudaBukhsh@nottingham.ac.uk)

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