Tim Howes is a Senior Data Scientist with a decade of experience at the intersection of genomics, computational biology, and statistical machine learning, currently focused on clinical evidence at the FDA. He led genomic biomarker discovery and reproducible analysis infrastructure for cancer immunotherapy at the Parker Institute and has a strong academic pedigree (PhD Stanford, MPhil Cambridge) grounded in experimental work on developmental genetics. Tim combines hands-on modeling and pipeline engineering with collaborative data curation for clinical-scale projects, and has taught causal inference to practitioners. He is equally comfortable interpreting high-throughput sequencing data and building the reproducible systems that make those insights actionable, and brings an evolutionary biology perspective to biomedical inference that informs both feature design and study interpretation.
10 years of coding experience
7 years of employment as a software developer
M.Phil Computational Biology, M.Phil Computational Biology at University of Cambridge
B.S. Chemical Engineering, B.S. Chemical Engineering at Michigan State University
Ph.D Chemical and Systems Biology, Ph.D Chemical and Systems Biology at Stanford University
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