Advanced Monte Carlo methods for glassy dynamics and complex materials
This is a fully-funded 4-year PhD position based in the HetSys Centre for Doctoral Training at the University of Warwick.
Project outline
Glasses are materials that combine macroscopic solid behaviour with amorphous liquid-like structure. These mysterious signature properties are ubiquitous across science and engineering, with examples ranging from optical fibres to novel formulations of pharmaceutical drugs and beyond.
Understanding these materials experimentally is, however, a real challenge due to very long relaxation timescales that preclude many experimental measurements. Modelling is therefore paramount, but traditional simulations are plagued by the same slow relaxational dynamics.
Through collaboration across Engineering, Statistics and Chemistry, this project will develop state-of-the-art simulation algorithms to circumvent the slow dynamics leading to high-quality modelling of currently inaccessible experimental quantities.
Supervisors
Primary: Dr Michael Faulkner (Engineering)
Prof. Gabriele Sosso (Chemistry)
Prof. Gareth Roberts (Statistics)
Event-chain Monte Carlo provides an opportunity to circumvent the slow dynamics. This rejection-free Monte Carlo algorithm advances particles along ballistic-style trajectories, without the constraints of physical dynamics. This leads to significant freedom when choosing the particle dynamics, with certain choices recently shown to circumvent analogous challenges in a foundational model. Moreover, the concept of teleportation portals instantaneously translates particles through one other. This project will develop and unify the two techniques for glasses, leading to rapid particle rearrangement/relaxation central to access to the key experimental quantities. We also aim to develop AI frameworks to characterise the power of the technique.
The principal outcome of this project will be an advanced computational technique for simulating glassy systems a foundational challenge with broad relevance across computational science and engineering. The development of this novel technique will lead to new software, which will be released open-source on GitHub with rigorous documentation. We also anticipate publishing 2-3 peer-reviewed journal articles. The student will also present their work at conferences and workshops and we hope to discuss our outputs with experimentalists.
- Version-control/code-documentation skills (key practices in professional software engineering evidenced by open-source software and documentation on GitHub).
- Modern object-oriented programming skills in Python (with Fortran).
- Strong knowledge and experience in high-performance computing (also through the formal training).
- A deep mathematical understanding of stochastic processes and Monte Carlo sampling central to high-quality data science, machine learning and AI.
- Uncertainty quantification, a key skill in computational science and predictive modelling.
- Teamworking will be developed during this collaborative project.
- Writing and presentation skills will be developed while writing journal articles and presenting results to the community.
These skills position you for careers in AI research, computational materials science, national laboratories, tech industry or academic research. The HetSys training provides a foundation for these skills through dedicated courses and cohort activities.
We require at least a II(i) honours degree at BSc or an integrated masters degree (e.g. MPhys, MChem, MSci, MEng etc.) in a physical sciences, mathematics or engineering discipline. We do not accept applications from existing PhD holders.
If you are an overseas candidate please check here that you hold the equivalent grades before applying.
For postgraduate study in HetSys, the term “overseas” or “international” student refers to anyone who does not qualify for UK home fee status. This includes applicants from the European Union (EU), European Economic Area (EEA), and Switzerland, unless they hold settled or pre-settled status under the UK’s EU Settlement Scheme.
If you are a European applicant without UK residency or immigration status that qualifies you for home fees, you will be classified as an overseas student.