82 parallel-and-distributed-computing-phd Postdoctoral positions at Stanford University
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Qualifications: A PhD in biology, neuroscience, development, or a related field. At least one first-author publication. Experience with iPS cells is preferred but not mandatory. Required Application Materials: CV
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the evolution of resistance to anti-cancer therapies. Developmental Cell. doi.org/10.1016/j.devcel.2021.07.009. Required Qualifications: A PhD in biology, genetics, development, neuroscience, or a related field
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. Experience in organizing and participating in workshops and conferences is a plus. PhD: A PhD in Economics, Computer Science, or a related field, with the Doctorate conferred before the start date. Required
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of behavior. Required Qualifications: a PhD (must be conferred before appointment start date) research experience in a related field at least one peer reviewed scientific publication able to collaborate in
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Scientist Training Enhancement Program (BD-STEP) at VA Palo Alto Health Care System Competitively selected Stanford postdoctoral fellows work with VA Medical Center clinicians and interdisciplinary
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, Major Depressive Disorder, and Dementia with Lewy Bodies. Required Qualifications: PhD in Neuroscience, Biomedical Engineering or related disciplines with expertise in data sciences Experience in
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programming background Experience in computer vision projects Experience in software or webapp development/API integration Interest (but not necessarily expertise) in medicine and radiotherapy Required
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benefits: Competitive and commensurate with experience; full Stanford benefits included. Required Qualifications: What We’re Looking For: • PhD or equivalent in Neuroscience, Cognitive Science, Computer
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are seeking a highly motivated, collaborative, and independent Postdoctoral Researcher to spearhead a research program within the general areas of synthetic genomics and synthetic biology, as
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. Required Qualifications: PhD in Computer Science, AI/ML, Computational Biology, or a related quantitative field. Proven expertise in deep generative modeling and large-scale multimodal learning. Experience