Project Spotlight: Exciting Opportunities for October 2025
We are thrilled to showcase some of our exceptional projects, open for home students for an October 2025 start.
These fully funded opportunities offer a stipend (£20,780 25/26 UKRI rate) to cover living expenses, as well as a generous research support budget.
In parallel with these projects, HetSys' renowned training programme is designed to equip students with the skills necessary to become high-quality computational scientists. Through this programme, participants will gain the ability to work seamlessly in interdisciplinary teams, sharpen their communication skills, and be well-prepared for diverse careers in fields where demand for expertise continues to grow.
If you're ready to engage in cutting-edge research and build a career, we encourage you to explore these opportunities.
To see our full range of projects click here.
| Projects | Summary |
|---|---|
| Artificial Intelligence-Assisted Modelling of High-Rate Ductile Fracture Supervisors: Dr Emmanouil Kakouris, Engineering 
|
When materials such as metal are subjected to sudden loads, for example, during an explosion, they can bend and stretch before breaking. This type of failure is difficult to predict because many processes occur simultaneously within the material. This PhD project aims to improve how we model and understand material failure. You will use state-of-the-art computational modelling techniques to develop more accurate computer simulations and apply Artificial Intelligence (AI) to enhance their precision and reliability. |
| Machine Learning-Driven Molecular Simulations of Gas Transport in Polymeric Materials Supervisors: Prof. Gabriele Sosso, Chemistry 
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This project utilises advancing machine learning techniques for simulating gas transport in polymeric materials. Specifically, we will leverage the MACE machine learning interatomic potential framework to improve the current models of gas diffusion and solubility in polymers, thus addressing several industry-relevant challenges. In particular, we seek to understand how aging affects these materials. The work involves molecular dynamics simulations, electronic structure calculations, and machine learning to develop accurate and efficient models. This project will lead to a robust computational framework to predict material behaviour and degradation over time. |
| Unlocking the Mysteries of Metallic Phase Transitions Supervisors: Dr Livia Partay, Chemistry 
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Join a PhD project that goes beyond state-of-the-art to explore the intriguing phase behaviour of potassium and unlock new understanding of alkali metals’ unique physical properties. At high pressures and temperatures, these metals reveal complex phase transitions that remain poorly understood with exotic structures emerging that are not seen in any other material. This project combines cutting-edge sampling techniques with machine-learned potentials for accurate phase predictions, offering considerable opportunity for method development with broad, long-term impact. Not only will you gain insights into fundamental atomistic properties of alkali metals, but you’ll also contribute to pioneering computational tools that extend far beyond potassium. |