Sami Chaaban is an investigator scientist and structural biologist based in Cambridge with eight years of experience deciphering the architecture and mechanisms of large protein assemblies using biochemistry, cryo-EM, and single-molecule fluorescence. He has led high-impact structural projects—such as solving the ~4 MDa dynein–dynactin complex—and integrates method development with computational tool creation to streamline cryo-EM and fluorescence workflows. Sami also applies protein design to engineer de novo binders that modulate cellular targets and improve cryo-EM detection, bridging wet-lab experimentation and in silico prediction. He champions best practices for structure prediction (AlphaFold) across his institute and has a track record of mentoring students and deploying research software on HPC clusters. Notably, his work combines deep mechanistic insight into cytoskeletal dynamics with practical software engineering to accelerate reproducible structural biology.
8 years of coding experience
Doctor of Philosophy (PhD) Cellular and Molecular Biology, Doctor of Philosophy (PhD) Cellular and Molecular Biology at McGill University
Contributions:1 release, 8 pushes, 1 branch in 2 years 4 months
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