PhD Studentship: Advanced Monte Carlo for Rapid Atomistic Simulations in Materials and Protein Folding University of Warwick in United Kingdom

[UK tuition fees covered plus a tax-free stipend of £21,805 at the UKRI rate for 3.5 years. International candidates must cover the difference in fee levels.]

This PhD studentship at the University of Warwick offers an exciting opportunity to develop advanced Monte Carlo simulation algorithms for rapid atomistic simulations, targeting both complex materials and protein folding. Many scientific challenges, such as rare transitions between stable states in proteins and materials, require highly accelerated computational techniques. The project is based on event-chain Monte Carlo, a rejection-free algorithm that advances particles along ballistic-style trajectories, enabling significant flexibility in particle dynamics. Recent advances in rejection-free tempering approaches further accelerate the exploration of crystal structures and protein folding configurations.

The research will unify these two key techniques and apply them to multimodal systems, including materials with different crystalline phases and protein folding—a foundational challenge in computational science and engineering. The project will also develop AI frameworks to characterize the power of these simulation methods. Outcomes include the creation of novel open-source software, rigorous documentation, and the publication of 2-3 peer-reviewed journal articles. The student will have opportunities to present their work at conferences and workshops and engage with experimentalists.

This studentship is hosted by the Warwick Centre for Predictive Modelling and involves collaboration with world-leading Monte Carlo experts in Warwick Statistics. The skills acquired will prepare you for careers in AI research, computational materials science, data science, national laboratories, the tech industry, or academic research.

Funding: The award covers UK tuition fees and provides a tax-free stipend of £21,805 at the UKRI rate for 3.5 years. International candidates are welcome but must cover the difference in fee levels.

Eligibility: Applicants should have a first or strong 2:1 honours degree in physics, mathematics, statistics, or a similar field. An MSc or equivalent is preferred. Experience with numerical programming in statistical physics and/or Bayesian computation is desirable.

Application Process: Submit an expression of interest by sending a CV and supporting statement outlining your skills and interests via the 'Apply' button. If successful, you will be invited to submit a formal application. Informal enquiries can be sent to Dr Michael Faulkner at [email protected].

Deadline: Applications must be submitted by 31 July 2026.