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states, tissue organization, and biological programs, and connect these representations to mechanisms of human disease. Your work will sit at the intersection of machine learning, computational biology
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discovery through public and Novartis-internal datasets. We are looking for candidates with A PhD in machine learning, computer science, computational biology, or a closely related field (completed or near
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 14 hours ago
motivated candidate with a strong interest in machine learning and clinical neuroscience. The lab studies resilience and vulnerability in brain aging and dementia, and builds computer-aided methods and tools
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identify the cells, cellular states, and biological programs through which genetic variation influences disease. Your work will sit at the intersection of statistical genetics, machine learning, and
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. The ideal candidate will possess not only a deep conceptual understanding of neuroscience but also advanced technical expertise in machine learning, artificial intelligence, and data modeling approaches. We
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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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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 16 hours ago
performance utilizing a variety of tools including life-cycle assessment (LCA), machine learning techniques, and/or optimization methods. This position will carry out state of the art research into the economic
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 14 hours ago
the nation for federal research expenditures as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital role in our
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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 13 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