Mick Ward
Machine Learning Scientist II at Generate:Biomedicines
Cambridge, Massachusetts, United States
Summary
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Rockstar🎓
Top SchoolMick 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.
10 years of coding experience
4 years of employment as a software developer
Master's Degree Molecular and Cell Bio, Master's Degree Molecular and Cell Bio at University of ConnecticutDoctor of Philosophy - PhD Computational Systems Biology, Doctor of Philosophy - PhD Computational Systems Biology at Washington University School of Medicine in St. Louis
Github Skills (22)
protein-sequences10
folding10
structural-biology9
biophysics9
computational-biology9
clustering8
cheminformatics8
rdkit8
exploratory7
bioinformatics7
ensembles7
react7
python7
protein-structure7
modeling6
Programming languages (3)
Github contributions (5)
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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