John Jumper
Distinguished Scientist at Google DeepMind
United Kingdom
Summary
👤
Senior🎓
Top SchoolJohn Jumper is a research fellow at Google DeepMind with 11 years of experience building state-of-the-art AI methods for scientific problems, particularly in protein modeling and molecular simulation. He progressed through research and leadership roles at DeepMind—from Research Scientist to Fellow—and holds a PhD in Theoretical Chemistry from the University of Chicago where he developed a fast, ML-driven protein simulation engine and sampling methods that outperform prior approaches by orders of magnitude. His background combines rigorous theoretical physics and high-performance software engineering (C++, OpenMP, SIMD) with practical tools for differentiable simulation developed earlier at D. E. Shaw Research. John’s work emphasises marrying generative models and graphical approximations to accelerate and interpret protein folding and side-chain prediction, and he has a track record of mentoring others to adopt his software in multiple publications. Based in the UK, he brings a rare blend of deep scientific insight and production-grade systems design that translates complex biophysical problems into scalable ML solutions.
11 years of coding experience
10 years of employment as a software developer
MPhil Theoretical Condensed Matter Physics, MPhil Theoretical Condensed Matter Physics at University of CambridgeBachelor of Science (BS) Mathematics Physics, Bachelor of Science (BS) Mathematics Physics at Vanderbilt UniversityDoctor of Philosophy (PhD) Theoretical Chemistry, Doctor of Philosophy (PhD) Theoretical Chemistry at University of Chicago
Stackoverflow
766reputation
79kreached
6answers
0questions
python
top-5%
Github Skills (30)
python9
gpu9
deep-learning8
pdb-files8
machine-learning8
neural-network7
dynamics7
numpy7
tensorflow7
pdb7
string-length6
gpu-acceleration6
scientific-computing6
combinations6
tensor6
Programming languages (2)
Github contributions (5)
John-Jumper/Upside-MD
Oct 2014 - Sep 2017
Contributions:391 commits, 8 pushes, 3 branches in 2 years 11 months
mdtraj/mdtraj
Dec 2016 - Feb 2017
An open library for the analysis of molecular dynamics trajectories
Contributions:5 comments, 1 issue in 1 month
pythonmdtrajmolecular-dynamicspdbpdb-files
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