85 computer-science-programming-languages-"St"-"ST" Postdoctoral positions at Stanford University
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: Epidemiology, Biomedical Informatics, Biostatistics, Public Health, Computer Science, Health Services Research, or a related discipline Strong quantitative and analytical skills, with proficient programming
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backgrounds trained in chemistry, chemical biology, microbiology, and/or biophysics fields. We have launched a collaborative antibacterial drug design program integrating chemical biology and mechanistic
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immunology. Preferred qualifications: Experience in immunology, human immunology, mammalian cell culture, multi-color flow cytometry, cell sorting, gene transfer, murine models, computational biology, and
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Posted on Wed, 02/12/2025 - 13:20 Important Info Deprecated / Faculty Sponsor (Last, First Name): Han, Summer Stanford Departments and Centers: Medicine, Biomedical Informatics Research (BMIR
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preparation and dissemination of findings at national and international conferences. Collaborate with investigators across rheumatology, pain medicine, biostatistics, informatics, and behavioral science
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Science. Proficiency in programming (Python, Julia), and high-performance computing (provide evidence with specific examples) Ability to work independently and collaboratively. Strong written and oral communication
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their knowledge and skillset in mitochondrial biology would best fit this position. Required Qualifications: PhD in cell biology, molecular biology, stem cell biology, developmental biology, immunology, or cancer
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embryos This Human Frontier Science Program (HFSP) (link is external) funded project is in collaboration with the labs of Hervé Turlier (CIRB-CNRS) and Chema Martin (Queen Mary University of London). We
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a PhD in the field of molecular and cellular cancer biology, relevant publications, curiosity for science and innovative thinking, and high fluency in English. Experience with mammalian cell culture
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for healthcare. The Alsentzer Lab is an interdisciplinary research group in the Department of Biomedical Data Science at Stanford University. Our mission is to leverage machine learning (ML) and natural language