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Stanford University required minimum for all postdoctoral scholars appointed through the Office of Postdoctoral Affairs. The FY25 minimum is $76,383. Deep Phenotyping of Learning Differences The high-level
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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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protein engineering techniques. In parallel, we are also looking for postdocs interested in developing high-throughput screens for single-domain antibodies, called nanobodies, that perturb intracellular
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transmission modeling, statistical modeling, spatial data analysis, and cost-effectiveness analysis. In parallel, we conduct research on vaccine-preventable infections, developing and evaluating predictive
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to establishing an Asian American Cohort funded by the National Institute of Health. Under the direction of the PI and program managers, the Research Assistant will provide administrative support for the study. Key
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(link is external) program and the initiative on Learning Differences and the Future of Special Education (link is external) ) gain partnership experiences with practitioners and policymakers (via
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. At single cell level, how does the same genome give rise to thousands of different cellular phenotypes in the brain? 2. At the tissue level, how do gene networks orchestrate intercellular communication
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to establishing an Asian American Cohort funded by the National Institute of Health. Under the direction of the PI and program managers, the Research Assistant will provide administrative support for the study. Key
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Posted on Tue, 03/04/2025 - 15:09 Important Info Deprecated / Faculty Sponsor (Last, First Name): Bohg, Jeannette Stanford Departments and Centers: Computer Science Postdoc Appointment Term: 2025
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variety of simulation and optimization techniques. Key areas of interest may include control theory, robust optimization, or distributed optimization. 2. The second candidate will focus on applied research