Charles Bury is an Associate Director of Data Science with 11 years' experience applying computational methods to drug discovery and de novo AI enzyme design from Oxford. He has progressed through technical and leadership roles at Exscientia and Medicines Discovery Catapult, bridging cheminformatics, discovery data science, and production-focused ML workflows. Trained as a DPhil systems structural biologist and MMath mathematician, he brings rigorous quantitative foundations to model-driven enzyme and small-molecule discovery. Colleagues rely on him to operationalize research tools—he maintained and released community software like RADDOSE-3D during his academic tenure—while scaling teams and pipelines in industry. Based in Oxford, he combines academic depth with practical product delivery, often translating crystallography and biophysics insights into deployable data-science solutions. Notably, his background spans open-source stewardship, end-to-end discovery analytics, and hands-on algorithm development for bioscience applications.
11 years of coding experience
6 years of employment as a software developer
DPhil in Systems Biology DTC Structural Biology, DPhil in Systems Biology DTC Structural Biology at University of Oxford
The King's School Chester
MMath Master of Mathematics (with honours) Mathematics, MMath Master of Mathematics (with honours) Mathematics at University of Warwick
A collection of python scripts to calculate per-atom damage metrics of electron density loss, derived from Fobs(n) - Fobs(1) Fourier difference maps, given an MX damage series collected on a single crystal. See the README.md below for run details.
Contributions:12 PRs, 203 pushes, 1 tag in 2 years 6 months
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