57 postdoc-computational-fluid-dynamics Postdoctoral positions at Stanford University
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are linked to the California Cancer Registry, as part of the national SEER registries. The postdoc fellow will work closely with statisticians, computer scientists, oncologists, and epidemiologists in the lab
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scientists, and clinicians provides a rare, exciting opportunity to develop methods that will directly contribute to improvements in patient care. The postdoc will become part of a research team supporting
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collected from different sources (e.g., self-report surveys, GPS, phone metadata). The postdoc will use computational methods to process and interpret multi-modal behavioral and contextual data collected from
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work within a thriving and inter-disciplinary team of faculty investigators, postdocs, research coordinators and clinicians. The expectation will be that the post-doctoral scientist leads imaging data
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work within a thriving and inter-disciplinary team of faculty investigators, postdocs, research coordinators and clinicians. The expectation will be that the post-doctoral scientist leads imaging data
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governance. The postdoc would be housed at the Stanford Institute for Human-Centered AI , jointly advised by Professor Percy Liang (computer science / Center for Research on Foundation Models ) and Professor
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, simulating real world settings and looking at fairness and generalizability. In particular, a background in computer vision and human-AI interaction is best suited for this role and project. Postdocs will have
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across the country. A key goal is to ensure that the postdoc is able to establish some projects for subsequent publication or creation of a new research program. SCALE is committed to creating a diverse
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from data. Toward a more systematic approach, we have introduced DSPy, a programming model that abstracts FM pipelines as imperative computation graphs. DSPy modules are parameterized, meaning they can
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-admins/how-appoint-postdocs for eligibility requirements. We look forward to hearing from promising candidates excited to advance turbulence research through computational methods and interdisciplinary