Samuel Sledzieski, Ph.D.

Samuel Sledzieski joined the Center for Computational Biology in September 2024, as a bridge Flatiron Research Fellow between the Structural and Molecular Biophysics and Genomics groups. His research is focused on context-dependent modeling of allosteric interactions and protein structural dynamics. He received his Ph.D. and M.S. from the Massachusetts Institute of Technology (MIT), where he developed high-throughput machine-learning methods to predict protein-protein interactions and drug-target interactions using protein language models. He received his B.S. from the University of Connecticut in 2019, where he worked on phylogenetic inference and error correction for modeling viral transmission. His Ph.D. work was supported by a National Science Foundation (NSF) Graduate Research Fellowship.