Summary
Matthew Suderman is a computational epigenetics researcher with 11 years of experience applying bioinformatics and statistical genomics to population health questions. Currently a research assistant at the University of Bristol, he integrates Illumina HM450k epigenome-wide analyses with richly phenotyped longitudinal cohorts (e.g., ALSPAC) to identify DNA methylation signatures linking early-life adversity to later health outcomes. Trained as a computer scientist (PhD, McGill) with prior roles as a bioinformatician and lecturer, he combines rigorous algorithmic thinking with practical wet-lab–scale data analysis. His work uniquely targets easily accessible cell types (T cells, buccal cells) to develop molecular markers for at-risk children and to evaluate intervention effects over time. Matthew also pursues mechanistic follow-up in animal models to translate predictive loci into actionable biology.
11 years of coding experience
8 years of employment as a software developer
Master of Science (M.Sc.), Computer Science, Master of Science (M.Sc.), Computer Science at Simon Fraser University
Bachelor of Science (B.Sc.), Computational and Applied Mathematics, Bachelor of Science (B.Sc.), Computational and Applied Mathematics at Trinity Western University
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at McGill University