Paul Kim is a Graduate Research Assistant at the Institute for Protein Design at the University of Washington, where Paul works on machine learning models for rational protein design. Paul is also a Software Engineer at the New York Structural Biology Center, focusing on developing machine learning algorithms for microscope navigation. In the past, Paul has worked at Bayer as a Bioinformatics - Machine Learning Researcher, where Paul explored novel methods for protein embeddings and developed Proteo-Chemometric protein-ligand binding models. Paul holds a Bachelor of Arts in Statistics from the University of California, Berkeley, and is currently pursuing a PhD in Molecular Engineering at the University of Washington.
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New York Structural Biology Center
NYSBC is a global leader in structural biology with unsurpassed instrumentation and expertise, providing biomedical research services to commercial and academic clients, including high throughput gene-to-structure determination, structure-based drug design, X-ray crystallography, NMR spectroscopy, cryo-electron microscopy and protein production.