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williamdavie/README.md

Supported by the NDA, my PhD’s core focus is the behaviour of helium in plutonium dioxide (Article), a system with strong electronic correlations that give rise to unconventional and exciting physics. I investigate how to train machine-learned interatomic potentials capable of capturing the exotic behaviour of plutonium and other strongly correlated materials.

Broadly, my interests lie in many-body quantum theory and in developing computational tools and algorithms for atomistic modelling, including improving the accuracy and training of machine-learning models.

William Davie, willdavie2002@gmail.com.

Department of Material Science and Metallurgy, University of Cambridge.

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  1. mace mace Public

    Forked from ACEsuit/mace

    MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.

    Python