Kyujung Jun is an assistant professor and computational materials scientist with eight years of experience modeling ion transport and machine-learned interatomic potentials, most recently as a postdoc in Rafael Gómez-Bombarelli’s group at MIT. His Ph.D. work at UC Berkeley developed neural-network force fields and identified structural descriptors that unlocked numerous new frameworks for fast lithium-ion diffusion in inorganic superionic conductors. He combines first-principles calculations, molecular dynamics, and bespoke algorithms—including a quaternion-based method to quantify anion rotations—to correlate rotational dynamics with lithium hopping mechanisms. Based in Cambridge, MA, he brings a rare blend of algorithmic innovation and physical insight aimed at accelerating electrolyte design for solid-state batteries.
8 years of coding experience
9 years of employment as a software developer
Ph.D., Materials Science and Engineering, Ph.D., Materials Science and Engineering at University of California, Berkeley
Bachelor of Science - BS, Nuclear Engineering, Materials Science and Engineering, Bachelor of Science - BS, Nuclear Engineering, Materials Science and Engineering at Seoul National University
Contributions:4 commits, 3 pushes, 1 branch in 1 year 3 months
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