67 parallel-computing-numerical-methods-"Simons-Foundation" Postdoctoral positions at Stanford University
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different disciplines and mentors Stanford Departments and Centers: Medicine, Biomedical Informatics Research (BMIR) Biomedical Data Sciences Postdoc Appointment Term: 1 year minimum with the option to extend
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common equipment, and also have the benefit of access to research facilities at Stanford University including core computing, microscopy, library, biostores, and analytical facilities. The Spin lab has
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immediately in the Department of Surgery at Stanford University. As part of the Asian Liver Center, our lab uses multidisciplinary approaches to identify and develop more efficacious methods for the diagnosis
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internal equity. Pay Range: 76,383-86,383 Our lab investigates the functional principles, development, and computational properties of organism-wide circuits for brain-body interactions. We
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., diffusion transformers, multimodal representation learning) for modeling high-dimensional biological images. Develop computational methods to reconstruct and simulate 3D tissue architecture and dynamics
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available immediately in the Molecular Imaging Program at Stanford (MIPS). The successful candidates will join a dynamic research group focusing on the development of peptide-based therapeutics and
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graduates of PhD programs in statistics, economics, computer science, operations research, or related data science fields. The position provides opportunities to participate in rigorous, quantitative research
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their own research program, under supervision of the principal investigator, as well as work across the many outstanding resources, institutes (e.g. Institute for Human-Centered AI) , and faculty labs across
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Substitution in the Blind; Ocular Structures and Physiology; MR Engineering and Methods Development for the Visual System. MRI experiments will mainly be conducted at research centers at the Stanford campus and
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. This includes integrating LLMs with structured data sources to develop robust computational phenotyping algorithms and scalable models for real-world evidence generation. The role will involve both method