Postdoc Biomedical AI ML Applications For Predicting Food Allergy & Salmonella Pathogenicity
Washington DC-Baltimore Area United States
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Summary
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Senior
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Top School
Ian Rambo is a computational biologist and postdoctoral fellow with over a decade of experience applying bioinformatics and biomedical AI/ML to problems in food allergy diagnostics and microbial ecology. At USDA ARS he develops transformer-based deep learning systems and scalable workflows in Python, R, and PyTorch to predict peanut and tree nut allergies and Salmonella pathogenicity from multi-terabyte genomic and clinical datasets. His work bridges bench and cloud—he pairs hands-on field and lab experience with HPC-enabled metagenomics, having characterized the first seven viruses of Asgard archaea during his Ph.D. and analyzed ~1 TB of viral metagenomes at JGI. He has a track record of translating complex omics into actionable biomarkers and published results, while also leading postdoc career development efforts. Ian balances technical rigor with creativity—he mentors, teaches programming workshops, and even composes D&D modules and fronts a folk band, reflecting strong collaboration and communication skills. Motivated by equitable healthcare, he focuses on reducing cost and time for allergy diagnostics through interpretable AI.
10 years of coding experience
Doctor of Philosophy - Ph.D., Marine Science, Doctor of Philosophy - Ph.D., Marine Science at The University of Texas at Austin
Bachelor of Science - BS, Biological Sciences, Cum Laude with Honors, Bachelor of Science - BS, Biological Sciences, Cum Laude with Honors at University of Rhode Island
Master of Science - MS, Marine Sciences, Master of Science - MS, Marine Sciences at University of Delaware
Contributions:210 pushes, 7 branches in 3 years 6 months
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