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Field
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imaging, genetics, omics, EHR data, and clinical outcomes. Ongoing work builds on deep-learning phenotypes from cardiovascular imaging at population scale and extends toward myocardial tissue remodeling
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SIT's mission is centred on nurturing industry-ready graduates who possess deep technical expertise and transferable skills to address future challenges. We collaborate with industry in our
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appointed through the Office of Postdoctoral Affairs. The FY27 minimum is $79, 056. Precision mapping of vector borne diseases using deep learning & high resolution remote sensing data Faculty in Stanford
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Post-Doctoral Position - Medical Image Processing - (240000Y9) Post-Doctoral Fellow Position in Medical Image Processing (Deep Learning for Trauma CT) The Trauma Radiology AI Lab (TRAIL) in
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to appointment start date We welcome candidates with deep expertise in one or more relevant areas, and a strong desire to learn across disciplines: Computational Biology: Spatial/single-cell omics, bioinformatics
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QUALIFICATIONS: PhD in computer science, electrical/biomedical engineering, statistics, applied mathematics, or a related field. Strong track record in machine learning/deep learning with imaging data
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and/or related fields including genetic epidemiology, human genetics, biostatistics, bioinformatics, computational biology, or phenomics (including EHR, deep medical imaging, and biomarker profiling