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for highly motivated postdoctoral candidates with a PhD in bioengineering deep knowledge in computational biology and machine learning. Candidates with a molecular biology or engineering degrees with
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monitoring systems, bedside monitoring devices, or medical device data. Experience linking physiologic waveform features to clinical outcomes. Experience with machine learning, deep learning, predictive
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field Demonstrated expertise in one or more of the following areas: Machine/deep learning, artificial intelligence, statistical modeling, or computational modeling Human neuroimaging analysis, including
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: The candidate must have a PhD and extensive experience in modern deep neural network-based techniques. The ideal candidate should have: A PhD and a strong record of research or applied work in deep learning, with
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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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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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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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equity. Pay Range: $81,000-85,000 Postdoctoral Scholar — Molecular Epidemiology and Integrative Multi-Omics of Cardiovascular Disease Dr. Themistocles (Tim) Assimes(link is external) , MD, PhD, FAHA