We advertise a four-year PhD position in the Centre of Doctoral Studies in Computational Methods for Materials Science, University of Cambridge. The position will be fully funded by the Atomic Weapons Establishment.

This is an opportunity to join one of the pioneering groups who actively develop and utilise machine learning methods to study materials on the atomistic level. This field is gaining momentum rapidly, with industrial partners showing keen interest in our applications.

The objective of the PhD project is to investigate and understand the differences between the thermodynamic and structural properties of solid Ti and the ternary alloy Ti-(6%wt)Al-(4%wt)V over the pressure range 0-250 GPa, at temperatures from 0K to the melting point.

The Gaussian Approximation Potential framework will be applied to accurately model the interactions on the atomic level for both pure Ti and the Ti-6Al-4V alloy. The resulting potential will be applied to calculate the elastic, thermodynamic and dislocation properties with ab initio accuracy for the first time.

The study combines the areas of density functional theory, machine learning and materials science. The ideal candidate will possess knowledge in two or more of these fields, as well as experience in programming.

The student undertaking this project will be supervised by Dr Shailesh Mehta from the Atomic Weapons Establishment, and Dr Albert Bartók-Pártay from the Department of Engineering. We note that the funding is subject to signing the project agreement between the University of Cambridge and AWE. Because of the nature of work associated with the post, it is subject to special nationality rules and is open only to British citizens. The selected candidate will be required to undergo security clearance.

Interested candidates should contact Albert Bartók-Pártay (ab686 at cam.ac.uk) directly.