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will have connections to both the Molecular Imaging Program at Stanford (MIPS) and the Radiological Sciences Laboratory (RSL). The ideal candidate for this position will have interest in being trained in
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, California 94305, United States of America [map ] Subject Areas: Applied Physics Chemistry Materials Science Quantum Optics Computer Science (more...) Quantum Gravity quantum gravity/quantum cosmology Quantum
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computational, experimental, observational, and theoretical approaches. Existing research programs at KIPAC span many areas of astrophysics and cosmology and include studies of dark energy and cosmic dynamics
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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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for Human and 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
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Posted on Mon, 08/04/2025 - 11:14 Important Info Deprecated / Faculty Sponsor (Last, First Name): Wolak, Frank Stanford Departments and Centers: FSI Program on Energy and Sustainable Development
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conducting policy-relevant empirical social science research. Designed for graduating seniors or recent college or master's program graduates, the fellowship provides a unique opportunity for those considering
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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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. She is also a faculty member in the Biophysics Program and a Faculty Fellow of the Sarafan ChEM-H (Chemistry, Engineering and Medicine for Human Health) Institute. Cegelski’s PhD in Chemistry and
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. Required Qualifications: PhD in statistics, economics, computer science, operations research, or related data science fields Strong data science skills, including experience working with large, complex data