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Fellows Program offers fellowships to outstanding new PhDs who have a demonstrated ability to generate high-quality, policy-relevant research on critical issues related to global development. We invite
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of this postdoctoral program is to conduct high-quality epidemiological research in the field of urological cancers with a special emphasis on kidney cancer epidemiology (including prevention and screening, control
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Prevention Research Center, an interdisciplinary research program on the prevention of chronic disease, is seeking MD, PhD, and other post-doctoral level applicants for research fellowships. Fellows gain
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to participate in the fellowship's community-building and professional development programs, complete annual progress reports, and meet their faculty advisors annual expectations. Appointment Start Date: September
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postdoctoral fellow with interest in organic chemistry and radiopharmaceutical development. Successful candidates will join the Molecular Imaging Program at Stanford within the Department of Radiology, Stanford
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/interdisciplinary-initiatives-program-seed-grant-enhancing-specialty-care (link is external) (2) Measuring, predicting, and implementing appropriate antibiotic use for common infections using electronic phenotyping
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, 2025 Group or Departmental Website: https://hai.stanford.edu/research/fellowship-programs/hai-postdoctoral-fellow-ad... (link is external) How to Submit Application Materials: For full consideration
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or Departmental Website: https://woods.stanford.edu/research/climate-and-energy-policy-program (link is external) https://bitsandwatts.stanford.edu/ (link is external) How to Submit Application Materials: Submit by
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steps using programs like Matlab or Python. *Other duties may also be assigned. DESIRED QUALIFICATIONS: Bachelor's degree in the sciences preferred. Excellent communication skills, especially the ability
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Biology, Bioinformatics, Computer Science, or a related field • Strong programming skills in R and/or Python • Experience with analysis of single-cell sequencing data • Familiarity with spatial