42 parallel-and-distributed-computing Postdoctoral research jobs at Duke University in United States
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The appointment is not part of a clinical training program, unless research training under the supervision of a senior mentor is the primary purpose of the appointment The Postdoctoral Appointee functions under
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guidelines for the Postdoctoral Appointee-mentor relationship. Prompt disclosure to the mentor regarding the possession and desire to distribute materials, reagents, software, copyrightable and potentially
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clinical training program, unless research training under the supervision of a senior mentor is the primary purpose of the appointment. The Postdoctoral Appointee functions under the supervision of a mentor
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may include teaching responsibilities. The appointment is generally preparatory for a full-time academic or research career. The appointment is not part of a clinical training program unless research
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may include teaching responsibilities. The appointment is generally preparatory for a full-time academic or research career. The appointment is not part of a clinical training program unless research
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research or scholarship. The appointment is generally preparatory for a full time academic or research career. The appointment is not part of a clinical training program, unless research training under
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may include teaching responsibilities. The appointment is generally preparatory for a full-time academic or research career. The appointment is not part of a clinical training program, unless research
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Duke University, Electrical and Computer Engineering Position ID: Duke -Electrical and Computer Engineering -POSTDOCYIRANCHEN [#30336] Position Title: Position Type: Postdoctoral Position Location
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or scholarship, and may include teaching responsibilities. The appointment is generally preparatory for a full time academic or research career. The appointment is not part of a clinical training program, unless
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simulations and multiscale spatial-omics data. • Integrate uncertainty quantification into scientific machine learning workflows and optimize the design of computational (ABM) and wet-lab experiments