Summary
Christian Seitz is a postdoctoral researcher blending chemistry, biophysics, and machine learning to tackle viral structure prediction and vaccine design. With a PhD in Biochemistry & Biophysics and eight years of interdisciplinary research, he has published first-author work spanning DFT, Brownian dynamics, molecular dynamics/Markov state models, and elastic network models applied to problems from organic reaction mechanisms to plant respiration and proto-nuclei. Currently based at the University of Chicago and Argonne, he holds competitive fellowships (NSF GRFP, NIH LRP) and secured an LDRD-SEED grant to benchmark protein structure prediction for the biophysics community. His background uniquely pairs quantum-chemical rigor with large-scale computational biophysics and emerging AI methods for pathogens, giving him a rare comfort shifting scales from electrons to epidemics.
8 years of coding experience
3 years of employment as a software developer
University of California San Diego
Bachelor’s Degree, Chemistry, 3.64, Bachelor’s Degree, Chemistry, 3.64 at Elon University
French, German, English