284 computer-programmer-"Multiple"-"U"-"O.P"-"FEMTO-ST-institute" positions at Stanford University
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exhibit a commitment to teaching and mentoring. The successful candidate must have a Ph.D. in statistics, data science, computer science, mathematics, or a related discipline at the time of appointment
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use fine light/fine grasping. Occasionally sit, reach above shoulders, perform desk based computer tasks, use a telephone and write by hand, lift, carry, push, and pull objects that weigh up to 40
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Assistant Professor, Department of Environmental Social Sciences (Environmental Behavioral Sciences)
movements, organizations/networks, collective action, political economy, population science. We are also interested in applicants who could teach computational social science for sustainability. Candidates
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world-class faculty and researchers who develop and employ cutting-edge technologies --from molecular to computational approaches-- to tackle fundamental questions in genetics. We foster a collaborative
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common equipment, and also have the benefit of access to research facilities at Stanford University including core computing, microscopy, library, biostores, and analytical facilities. The Spin lab has
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work on a priority research program in which individuals are assessed with functional MRI, behavioral, and symptom measures before, during, and after treatment. Treatment includes selectively targeted
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, economics, computer science, operations research, or related data science fields. The position provides opportunities to participate in rigorous, quantitative research on human trafficking, including supply
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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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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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include, but are not limited to, using the latest computational learning-driven approaches, including computational social science, foundation models and multimodal machine learning, to enhance