Summary
Shikai Jin is a data scientist in the San Francisco Bay Area with a Ph.D. in Biology and nine years of experience applying computational and AI methods to biophysics and structural biology. He has published extensively on protein folding, structure prediction, and protein-protein interactions, and brings hands-on expertise in X-ray crystallography, cryo-EM, and enzyme design using Rosetta. Comfortable across Python, C/C++, ML frameworks (PyTorch, TensorFlow), molecular dynamics (Gromacs, OpenMM), and AlphaFold-related tools, he bridges wet-lab structural techniques with deep learning approaches to tackle hard biological problems such as the phase problem. Currently at Gilead Sciences after a productive Ph.D. at Rice University, he combines rapid learning, strong organizational skills, and multi-project management to move projects from idea to production. Outside work he pursues diverse interests from badminton to plant identification, reflecting a curious, cross-disciplinary mindset that fuels unconventional solutions.
9 years of coding experience
6 years of employment as a software developer
Master's degree, Master's degree at Rice University
Bachelor of Science - BS, Bachelor of Science - BS at Zhejiang University
Japanese, Chinese, English