Summary
Eric Kernfeld is a research scientist and statistician specializing in computational biology and genomic data analysis, with 11 years of hands-on experience across academia and industry. He recently completed a PhD in Biomedical Engineering at Johns Hopkins focused on neutral evaluation of transcriptional regulation models and has driven projects from raw sequencing reads to published papers using scRNA-seq, scATAC-seq, Hi-C, Perturb-seq, and CRISPR screens. Eric pairs rigorous statistical training (MS in Statistics) and a strong math background with practical software engineering habits, keeping analysis infrastructure well-organized to avoid technical debt in fast-moving research. He has a track record of translating complex experimental transitions into robust, documented pipelines—most notably helping a startup navigate sequencing-technology changes—and has led data-driven discoveries in stem cell genomics. Based in Boston, he is seeking roles in machine learning, bioinformatics, or computational biology where he can combine inventive modeling with reproducible data engineering.
11 years of coding experience
4 years of employment as a software developer
Master of Science - MS, Statistics, Master of Science - MS, Statistics at University of Washington
Johns Hopkins University
B.S., Mathematics, 3.92/4, B.S., Mathematics, 3.92/4 at Tufts University