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diseases using deep learning & high resolution remote sensing data Faculty in Stanford Medicine are seeking to appoint a Postdoctoral Research Fellow to join a project developing and validating deep
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UCSF, Division of Cardiology, Pirruccello Lab | San Francisco, California | United States | 19 days ago
cutting-edge research at the intersection of cardiovascular genetics, deep learning, and epidemiology . The Pirruccello Lab at UCSF/CVRI is interested in understanding the drivers of normal
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machine learning, deep learning, foundation models/LLM. Excellent quantitative and analytical skills. Strong written and interpersonal communication skills. Strong motivation & ability to work
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collection settings (preschools, homes) using a variety of methods (child-centered wearables, deep learning, fNIRS, eyetracking). The postdoc will primarily be mentored by Meg Cychosz (Linguistics), but
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RNA-seq, ATAC-seq, and multiome datasets related to heart failure and cardiovascular biology. Develop and apply machine-learning and deep-learning approaches to identify disease-associated
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engineering, statistics, applied mathematics, or a related field. Strong track record in machine learning/deep learning with imaging data; publications in medical imaging or health data science are highly
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, representation learning, mechanistic interpretability, concept-based explanation, or visual analytics for machine learning. Experience developing and applying deep learning methods at medium to large scale
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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 demonstrated ability to design, train, and deploy
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important problems in biology and medicine. We seek outstanding researchers with training in AI/machine learning, computer science, statistics, mathematics, physics, or related quantitative fields
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density in regulating these processes. The insights gained from these empirical studies will be paired with computational biology and machine learning to develop predictive AI models of how cells