Jason De Koning is an Associate Professor and computational genomics researcher with 11 years of professional experience translating evolutionary and population-genetics theory into scalable Bayesian and machine-learning inference for health genomics. Based at the University of Calgary, he leads graduate training and integrates computational molecular evolution with large-scale statistical methods to tackle complex genomic questions. His work spans academia and pedagogy—from directing computational genomics courses to postdoctoral research at the University of Colorado—and is documented in a prolific Google Scholar profile. Known for bridging theoretical population genetics and practical genomic inference, he combines a rare mix of deep quantitative training (PhD in Biological Sciences) and hands-on bioinformatics to drive reproducible, large-scale analyses.
11 years of coding experience
11 years of employment as a software developer
Biomathematics, Biomathematics at European Biomathematics Summer School (Termoli, Italy)
Ph.D., Biological Sciences, Ph.D., Biological Sciences at State University of New York at Albany
Complex Systems Summer School, Complex Systems Summer School at Santa Fe Institute
B.Sc., Biology and Computer Science, B.Sc., Biology and Computer Science at Trent University
Workshop on Molecular Evolution, Workshop on Molecular Evolution at Woods Hole Marine Biological Laboratories
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