Ron Schwessinger is a Senior AI/ML Engineer with a decade of experience translating deep learning research into functional genomics applications, currently applying these skills at GSK. He builds and scales neural networks that integrate DNA sequence, epigenomics and 3D chromatin architecture to predict gene regulation and interpret non-coding variation, work rooted in a PhD from Oxford. His background spans academia and industry—publishing models for megabase-scale chromatin prediction, developing single-cell expression predictors, and consulting on ML adoption—so he bridges novel method development with practical deployment. Based in Heidelberg, he combines strong computational skills (Python, TensorFlow) with hands-on genomics, and often supervises and mentors junior researchers, reflecting both technical depth and collaborative leadership.
10 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Genomic Medicine and Statistics, Doctor of Philosophy - PhD, Genomic Medicine and Statistics at University of Oxford
Master of Science - MS, Molecular Biology, Master of Science - MS, Molecular Biology at Heidelberg University
Bachelor of Science - BS, Molecular Biology, Bachelor of Science - BS, Molecular Biology at Ruprecht-Karls-Universität Heidelberg
Contributions:15 commits, 27 pushes, 1 branch in 1 year 7 months
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