Neil Dalchau is Head of Computational Biology with over a decade of industry research experience translating dynamical-systems theory and machine learning into practical biotechnology solutions. He has led teams at Microsoft Research and Synteny, published 40+ peer-reviewed papers, and built open-source tools (notably in F# and Python) to make advanced modeling reproducible and deployable. His work spans adaptive immunity modeling, DNA-based computation concepts, engineered pattern formation in cells, and process trade-offs in viral vector manufacturing, blending deep math with lab-aware automation. Known for connecting theoretical insight to product-relevant questions, he actively shapes which data should be collected to maximise experimental ROI. Based in Cambridge, UK, he combines a PhD-level quantitative background with hands-on software craft and a penchant for surprising crossovers between computation and wet lab systems.
11 years of coding experience
11 years of employment as a software developer
MMath Mathematics, MMath Mathematics at University of Oxford
PhD Mathematics Engineering Plant Sciences Biology, PhD Mathematics Engineering Plant Sciences Biology at University of Cambridge
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