Mick Ward

Senior Scientist I, Machine Learning at Generate:Biomedicines

New Haven, Connecticut, United States
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Summary

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Mick Ward is a Machine Learning Scientist II with 11 years of experience applying deep learning and molecular simulation to protein biophysics and drug discovery. With a PhD from Washington University School of Medicine, he adapted state-of-the-art graph neural networks to predict cryptic, druggable pockets and accelerated workflows by orders of magnitude while developing novel dimensionality-reduction and adaptive-sampling algorithms for massive molecular datasets. Currently at Generate:Biomedicines, he translates academic advances into production ML for therapeutic discovery and has hands-on experience working with exascale Folding@Home data and open-source tools like Enspara. Known for combining classical biophysics, CNNs, and search algorithms to predict metabolism and toxicity, he brings both experimental insight and scalable engineering to complex biological problems.
code11 years of coding experience
job6 years of employment as a software developer
bookMaster's Degree, Molecular and Cell Bio, Master's Degree, Molecular and Cell Bio at University of Connecticut
bookDoctor of Philosophy - PhD, Computational Systems Biology, Doctor of Philosophy - PhD, Computational Systems Biology at Washington University School of Medicine in St. Louis
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Github Skills (19)

protein-sequences10
structural-biology10
folding10
computational-biology10
biophysics9
clustering9
protein-structure8
python8
deep-learning8
neural-network7
rdkit7
data-structure7
cheminformatics7
react7
data-structures6

Programming languages (3)

JavaScriptHTMLPython

Github contributions (5)

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mizimmer90/slandscapes

Aug 2017 - May 2019

Contributions:18 commits, 3 pushes, 2 branches in 1 year 8 months
bowman-lab/diffnets

Dec 2019 - Jul 2021

Self-supervised neural nets to understand protein mutations
Contributions:120 commits, 3 PRs, 65 pushes in 1 year 7 months
superviseddeep-learningnetsneural-netsstructural-biology
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