66 computer-programmer-"https:" "https:" "Inserm" "Inserm" Postdoctoral positions at Duke University
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career. 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
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% to supervising and assisting PhD students. Qualifications • Candidates with a Ph.D. in any area of cognitive neuroscience broadly defined (e.g., Psychology, Neuroscience, Computer Science, or a related field) are
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excited about working in a diverse lab group setting, plan and conduct assessments independently and collaboratively, interpret data, and present results to diverse audiences. Fluency in English (written
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career. 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
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career. 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
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Program, and the field site in Kenya, and engage with investigators at all sites across various disciplines. The project will focus on conceptualizing, innovating, and implementing data-driven approaches
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this position; no new applications will be accepted after 2025/12/18 11:59PM US Eastern Time. Position Description Postdoctoral Associate in Synthetic/Medicinal Chemistry Location: The Hong Group (https
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all voices are heard. All members of our community have a responsibility to uphold these values. Application Materials Required: Further Info: http://www.bme.duke.edu http://www.bme.duke.edu
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discovery and computational tools. The successful applicant will lead a research project and will have the opportunity to mentor students. Candidates must hold a PhD or anticipate completion of a PhD prior to
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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