I did my undergraduate degree in Chemistry at Pembroke College (2018 – 2022) before starting a PhD in Machine Learning for Chemistry. I really loved my time at Pembroke as an undergrad and have always enjoyed teaching, so I am incredibly grateful for the opportunity to give back to the Pembroke Community and excited to support and inspire the next generation of Pembroke chemists. I teach Physical and Inorganic Chemistry to all three years of the undergraduate cohort.

I am currently a PhD student jointly supervised by Prof. Volker Deringer (Oxford) and Dr. Fausto Martelli (IBM Research). My research focusses on the use of machine learning to study amorphous materials. I use unsupervised and supervised learning to elucidate structure-property relationships in four-fold tetrahedral networks such as carbon, silicon and water.

Outside of chemistry, I’m a Blues athlete for the Oxford University Swimming Club and an Ironman Triathlete.

J.L.A. Gardner, Z. Faure Beaulieu, V.L. Deringer, Synthetic data enable experiments in atomistic machine learning, Digital Discovery, 2023, 2, 651

Z. Faure Beaulieu, T.C. Nicholas, J.L.A. Gardner, A.L. Goodwin, V.L. Deringer, Coarse-grained versus fully atomistic machine learning for zeolitic imidazolate frameworks, Chem. Commun., 2023, 59, 11405

Z. Faure Beaulieu, V.L. Deringer, F. Martelli, High-dimensional order parameters and neural network classifiers applied to amorphous ices, J. Chem. Phys., 2024, 160, 081101