| Qualification Type: | PhD |
|---|---|
| Location: | Coventry, University of Warwick |
| Funding for: | UK Students, EU Students, International Students |
| Funding amount: | £20,780 Stipend + Fees + Training Budget |
| Hours: | Full Time |
| Placed On: | 1st December 2025 |
|---|---|
| Closes: | 28th January 2026 |
| Reference: | HP-2026-015 |
About the project:
Machine Learning for Organic Materials: From Molecules to Mobility
Supervisor: Prof. Gabriele Sosso, University of Warwick
Accurately predicting how gases move through organic materials such as polymers underpins major challenges - from reducing hydrogen crossover in fuel cells to controlling gas transport that drives battery degradation. The key challenge is to build models that capture gas/polymer interactions and ageing with quantum-level accuracy at the larger scales of real materials.
This project will train machine-learning models on high-quality quantum data, use them for molecular simulations, and connect the results to continuum models via reproducible multiscale approaches. The focus will be on gas/polymer systems relevant to AWE-NST, a UK stakeholder promoting fundamental science with practical impact.
About HetSys: Harnessing Data, Modelling and Simulation for Real‑World Impact
HetSys (Centre for Doctoral Training in Modelling of Heterogeneous Systems) at the University of Warwick is an innovative, interdisciplinary fully funded PhD programme that brings together science, engineering, and mathematics to tackle some of the most pressing challenges of our time.
If you’re excited by the idea of using advanced modelling and simulation to solve complex, real‑world problems, HetSys offers the perfect environment to push boundaries and make a difference.
Funding:
Awards for UK, EU, International applicants cover full University fees, give a research training budget and a tax-free stipend to cover living costs (standard UKRI rate £20780 in 25/26 - equivalent to national living wage).
Closing Date: 28/01/2026
Please apply via the ‘Apply’ button above.
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