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for this position will be a highly motivated individual with experience in deep learning and medical imaging and a PhD degree in computer science, electrical and computer engineering, biomedical engineering
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for collaboratively analyzing scientific knowledge and Indigenous knowledge to inform multiple evidence base (MEB) policy-making; and, (3) proactively and responsively analyze governance architectures and policy
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of output from global climate models (CMIP-class models) as well as Integrated Assessment Models (IAMs) such as GCAM or PAGE. The candidate must have a PhD degree in a related field, be fluent in computer
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neural stimulation and/or computational neural modeling are required as are excellent communication skills. The Postdoctoral Appointee holds a PhD or equivalent doctorate (e.g. ScD, MD, DVM). Candidates
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outside Duke University. Preferred qualifications: PhD (completed in the last 1-5 years or PhD candidate) in a quantitative discipline, including Computational Biology, Bioinformatics, Computer
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collaborative environment at Duke is ideal for our multi-scale modeling research efforts. An earned PhD and previous experience in computational neurostimulation modeling are required as are excellent
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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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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 training
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responses to social experience and pheromone circuit activity in Drosophila. Applicants should hold a PhD in neuroscience or a related field and have experience working with Drosophila. We are particularly
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Program, the Nancy Grace Roman Space Telescope, the Rubin Observatory LSST, and the Simons Observatory. The Duke Cosmology group currently consists of about ten PhD students and seven postdocs or research