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Yale Analog and RF Circuits and Systems (ARCS) Research Group, Department of Electrical and Computer Engineering, Yale University The Analog and RF Circuits and Systems Research Group in
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scientists, and collaborators at academic and health-system sites nationally and internationally. The position is supported primarily through the DISCOVER-AI initiative, a three-year project within
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, design and analysis of virus-derived RNA libraries, and development of machine learning models for detecting functional elements in viral metagenomic datasets. This project is a collaboration with the
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the opportunity to collaborate with theorists and experimentalists in YQI and elsewhere working on a variety of topics of mutual interest. Current research interests include (but are not limited to): A
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biosafety level 2 (BSL2+) lab), immunology (such as flow cytometry and CAR-T engineering), molecular biology (such as CRISPR, RNA biology), or animal models, (e) collaboration with other researchers both
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. Position Overview The successful candidate will develop and apply advanced computational and machine learning methods to large-scale genomic, clinical, and imaging datasets, working across one or more of the
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themselves are hosted in their current repositories. The primary research goals include: Discovery of large-scale dataset repositories, and harvesting metadata from them, including the German NFDI network
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. Current research areas include environmental and lifestyle exposures, metabolic dysfunction, obesity, inflammation, proteomics, metabolomics, and other multi-omics approaches in relation to cancer and
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experimental approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory
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approach to public health research. Candidates with research experience working with people who use drugs and community organizations that serve this population are preferred. Having a car to drive to sites