83 computer-programmer-"Multiple"-"Prof"-"O.P"-"U" "U.S" Postdoctoral positions at Stanford University
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Computational Spatial Biology We are seeking a postdoctoral fellow in computational spatial biology to work in the laboratory of Professor Sylvia Plevritis in the Department of Biomedical Data Science at Stanford
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productivity, and the ability to work both independently and collaboratively in a multidisciplinary environment (involving clinicians, computer scientists, and statisticians). A strong background in
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, psychiatry, developmental psychopathology, neuroimaging research (MRI, fNIRS), engineering, computer science, or related fields. Required Qualifications: Doctoral degree (PhD, MD, or equivalent) conferred by
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learning to derive principled models of cortical computation. Our newly refurbished primate facility, state‑of‑the‑art Neuropixels rigs, and high‑performance computing cluster offer an unmatched playground
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. Ph.D. (ideally completion by Summer 2025) in computer science, statistics, operations research, or related fields. Prior experience working with data, including expertise with computational methods Prior
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for all postdoctoral scholars appointed through the Office of Postdoctoral Affairs. The FY25 minimum is $73,800. The Mackall Laboratory is seeking a creative and motivated computational immunologist to join
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cell biology including neuroscience, GPCRs or related techniques, and/or (3) computational biology are encouraged to apply. We welcome applications from women, minorities, and other underrepresented
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on manuscripts, presentations, and research proposals Required Qualifications: PhD in psychology, neuroscience, biostatistics, computer science, or a related field. Strong interpersonal and technical skills
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research. Proven experience with protocol development and research leadership. Excellent organizational skills and the ability to maintain meticulous records. Ability to plan and prioritize own work to meet
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use of cutting-edge informatics to prioritize causal variants for validation using functional genomics, including CRISPR. The overall goals of this work are to define novel disease targets and context