264 parallel-and-distributed-computing-"Meta"-"Meta" positions at Stanford University in United States
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five years of relevant experience or combination of education and relevant experience. Demonstrated high-level administrative experience which includes advanced computer skills and demonstrated
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Requirements*: Ability to drive day or night. Ability to obtain and maintain a California Non-commercial Class C Driver's License. Frequently stand/walk, sitting, perform desk-based computer tasks, use a
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on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned. MINIMUM REQUIREMENTS: Education
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and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as
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Administrator or Clinical Research Coordinator preferred. * Current basic CPR (Basic Life Support/Provider) certification. PHYSICAL REQUIREMENTS*: * Frequently stand/walk, sit, perform desk-based computer tasks
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Postdoctoral position in Computational Immunology We are looking for two motivated postdoctoral researchers to work on human macrophage biology in the Department of Pathology at Stanford. Successful candidates
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, walk, twist, bend, stoop, squat and 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
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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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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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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