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Field
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within the Division of Artificial Medical Intelligence of Department of Ophthalmology in the University of Colorado School of Medicine. We focus broadly on quantitative and machine learning techniques in
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Previous Job Job Title CS&E Postdoc Next Job Apply for Job Job ID 376331 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular/Temporary Regular Job Code 9546 Employee Class Acad
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to iteratively refine models and optimize experimental design. Collaborate with another postdoc in the NIH Center to use scientific machine learning (SciML) to automatically select mathematical models from data
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
of microscopy, multiplexed immunofluorescence, spatial/protein imaging, or image-derived single-cell phenotypes. Machine learning, latent variable modeling, variational autoencoders, optimal transport, graph
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 5 days ago
world. Position Summary This Postdoctoral Research Associate will conduct advanced research in artificial intelligence, machine learning, computer vision, and medical image analysis. The position will contribute
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
world. Position Summary This Postdoctoral Research Associate will conduct advanced research in artificial intelligence, machine learning, computer vision, and medical image analysis. The position will contribute
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-Direct the Responsible Conduct of Research (RCR) Program for postdocs Partner with the Center for Bioethics to deliver the RCR Program. Teach RCR sessions using cutting edge pedagogical techniques
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and machine learning with density functional theory, or other similarly relevant computational methods, to advance understanding of materials design predictions for 2D and 3D systems with electronic and
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, learning, well-being, social experiences, and decision-making. HARP is developing a longitudinal multimodal research resource to study human-AI interaction and its impacts using student-informed, privacy
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interiors. This work will rely on large-scale atomistic simulations paired with machine-learning interatomic potentials. Duties: ● The postdoc will generate density functional theory reference data, use