Engineering and Physical Sciences Research Council Featured PhD Programmes
European Molecular Biology Laboratory (Heidelberg) Featured PhD Programmes

Spectral Methods for Inhomogeneous Radiation Chemistry


Department of Mathematics

, Applications accepted all year round Funded PhD Project (European/UK Students Only)

About the Project

The aim of this PhD project is to model phenomena in radiation chemistry which current state-of-the-art simulation techniques cannot predict. Real-world applications include safe radioactive waste disposal, plutonium stewardship and radiation-based cancer care.

High energy radiation-matter interactions are well modelled using a kinetic Monte Carlo simulation, the de-facto standard at institutions such as CERN. For some applications the behaviour of lower energy particles must be taken into account. However, the assumptions of kinetic Monte Carlo no longer apply, because at lower energies the particles interact with their environment in more complicated ways --- we must consider reactions (inhomogeneous in both space and time) and diffusion effects.

Mathematically speaking, the governing equations are reaction-diffusion equations. However, there are key challenges associated with solving these equations in this specific problem domain. This PhD project will explore Spectral Methods, which involve representing the solution to the differential equations in a basis of increasingly oscillatory modes. The proposed research will explore different types of basis, including techniques with the right balance of properties such as rate of approximation, computational complexity, and physical intuition.

This post will involve development and analysis of numerical algorithms with Dr Webb in the Department of Mathematics and Prof. Currell from the Department of Chemistry. It will also involve collaboration with members of the Dalton Cumbrian Facility, in particular working with realworld data from radiation experiments conducted there.

We are looking for an enthusiastic and motivated graduate with the following:
• Obtained or working towards a 1st class degree in Mathematics, or a closely related discipline with strong mathematical component such as Physics, Engineering, or Chemistry (Master’s level or equivalent)
• Background in some or all of the following: scientific computing, partial differential equations, numerical analysis
• Good programming skills in a language such as Matlab or Python
• Good communication skills (oral and written)
• Openness to working across disciplines

Interested candidates should email both Marcus Webb () and Fred Currell () in the first instance with a CV, cover letter, transcripts and contact details for 2 referees.

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