James is a Post-Doctoral Research Scientist at IBM Research UK, and part of the IBM research presence at the Science and Technology Facilities Council (STFC) in Daresbury UK.
James completed his doctoral studies at the University of St Andrews, Scotland, where his research focused on molecular property prediction, using a combination of quantum chemistry and machine learning methodologies. This research concentrated on the prediction of solubility, which is a critical parameter for many biologically active agents.
Following the successful completion of his PhD, he moved to the University of Manchester, to undertake research related to the creation of a novel polarizable force field (FFLUX) for biomolecular simulation. FFLUX, combines quantum mechanical energy partitioning, Interacting Quantum Atoms (IQA), with machine learning, aiming to provide an efficient and accurate methodology. This work focused on expanding the existing IQA theory and methodology to enable the partitioning of post-Hartree-Fock wave functions, and determine the energy contributions of dynamic electron correlation to chemical bonding. Having completed this, James explored machine learning predictions of dynamic electron correlation contributions.
James' primary research interests relate to modelling of condensed matter, molecular property prediction, and method development.