Jaycee Choi is a predoctoral associate and PhD candidate at The Jackson Laboratory applying machine learning and computer vision to quantify homeostatic mouse behaviors such as feeding and drinking. With 11 years of research experience spanning computational genomics and behavioral quantification, Jaycee blends statistical modeling of NGS and single-cell data with practical Python/R pipelines. Earlier work at La Sierra University produced first-author bioRxiv publications cataloguing SINE insertions in dogs and revealed SINE-driven polyadenylation in 3'UTRs, highlighting a knack for extracting biological insight from public genomic resources. Based in Bar Harbor, Maine, Jaycee combines rigorous mammalian genetics training with hands-on algorithm development to translate complex datasets into reproducible biological phenotypes. Colleagues note an ability to move seamlessly between statistical theory and applied computer vision, making them effective at bridging analytics and experimental labs.
11 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Mammalian Genetics at JAX, Doctor of Philosophy - PhD, Mammalian Genetics at JAX at Tufts University
Bachelor of Science - BS, Biology: Biological Sciences, Bachelor of Science - BS, Biology: Biological Sciences at La Sierra University
Contributions:26 commits, 41 pushes, 1 branch in 1 year 8 months
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