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these discoveries into new therapies and diagnostics. We employ cutting-edge approaches in genome engineering, synthetic biology, genomics, and computational biology to illuminate the regulatory networks governing
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learning platforms are preferred; Experience with computing in cloud environments is a strong plus; some experience with high performance computing and database administration is desired but not required. A
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, or multi-modal learning that integrates structured EHR and biomarker data. The fellow will have access to curated oncology datasets, high-performance computing infrastructure, and mentorship from a cross
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opportunities to work with leading experts, including: Wei Jin (Computer Science) Ben Lopman (Epidemiology) Katia Koelle (Biology/Virology) Postdocs will be supported in professional development, including
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mentorship from Dr. Max Lau, and opportunities to work with leading experts, including: Wei Jin (Computer Science) Ben Lopman (Epidemiology) Katia Koelle (Biology/Virology) Postdocs will be supported in
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, San Francisco, and has a strong and unique multi-disciplinary research background across both molecular and computational biology. Dr. Zhang has published first- and co-author papers in high-profile