75 parallel-computing-numerical-methods Postdoctoral positions at Stanford University
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-author papers and present at conferences with the goal of helping the Fellow continue to build out a robust program of research. Timeline Application review will begin January 30, 2025. Applicants
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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
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microinjection or targeted incubation. Developing and implementing novel strategies for an Adult Editing System, establishing robust Cas9/gRNA delivery methods for somatic cells in adult organisms. You will
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screening, high-content imaging, or functional assays of sensory or neuronal activity. · Computational or bioinformatics experience for analysis of omics data. Required Application Materials: 1. Cover letter
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activity. · Computational or bioinformatics experience for analysis of omics data. Required Application Materials: 1. Cover letter describing your background, programming experience, and research interests
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the population-level burden of aging-related diseases and serious illness. The Stanford Center for Longevity and Healthy Aging Postdoctoral Fellowship Program focuses on population sciences research that addresses
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substitution in the EGFRvIII peptide significantly increases survival in an animal model of glioblastoma by enhancing proteasomal processing. We also developed robust methods to detect a new class of non