66 parallel-computing-numerical-methods Postdoctoral positions at Stanford University
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assessment of lymphatic flow, 2) Advancing methods for contrast-enhanced MRL, 3) Creating ideal contrast agents for MRL, and 4) generating phantom and animal models for MRL optimization and validation
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Planetary Health (HPH) (link is external) and Project Unleaded (link is external) for an exciting postdoctoral fellowship that contributes to a high-impact global program with a mission to create a
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their appointment. Knowledge of theoretical and/or observational cosmology, particularly including perturbative methods, will be an asset. Candidates with a strong background in other theoretical or data analysis
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genomics and single-cell spatial transcriptomics, participate in T cell-targeted therapy development, hone their computational, leadership, communication, and funding acquisition skills, and join the vibrant
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backgrounds trained in chemistry, chemical biology, microbiology, and/or biophysics fields. We have launched a collaborative antibacterial drug design program integrating chemical biology and mechanistic
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preparation and dissemination of findings at national and international conferences. Collaborate with investigators across rheumatology, pain medicine, biostatistics, informatics, and behavioral science
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methods to improve prediction model generalizability, model fairness, and generalizability of fairness across different clinical sites. The researcher will have the opportunity to use machine learning and
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The Stanford Abdominal Diffusion Group is seeking thoughtful, motivated and collaborative postdoctoral fellows to join a growing team developing motion-robust multi-shot DWI methods for liver, pancreatic, and
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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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of the selected candidate, budget availability, and internal equity. Pay Range: $80,000-95,000 The Alsentzer Lab at Stanford is seeking a postdoctoral fellow to advance trustworthy, deployable AI methods