51 computer "https:" "https:" "https:" "https:" "https:" "UCL" Postdoctoral positions at Duke University
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multiple affiliations. Computational Immunobiology Postdoctoral Associate Position (Williams) Be You. The Duke Human Vaccine Institute (DHVI) continues to lead cutting edge vaccine research against
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brain evolution. We employ a multifaceted strategy to bridge developmental neurobiology, RNA biology, and evolution. Learn more about our interests, motivations and discoveries: https://sites.duke.edu
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Postdoctoral Associate, Computational Behavioral Analysis & Digital Autism Research Be You. At Duke, we celebrate individuality, innovation, and the unique perspectives that each member of our
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-throughput genomic screening approaches, primary cell culture systems, and animal models of influenza disease. For more information visit https://mgm.duke.edu/faculty-and-research/primary-faculty/nicholas
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and application of advanced computed tomography methods, with a focus on photon-counting CT, quantitative image analysis, and machine learning. The position will involve work across several NIH-funded
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Date: Nov. 1, 2026 Application Review Begins: Immediately Location: Durham, North Carolina Work Arrangement: On-site Salary: $65,000 Research Program Description
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computational immunology as part of the NIH/NIAID-funded Multiscale Immune System Modeling (MISM) Center. The postdoctoral associate will contribute to and participate in meetings, workshops, trainings
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for postdoctoral fellows. We are seeking highly motivated candidates to join our research program in regeneration genomics. Our laboratory develops and applies cutting-edge genomics and proteomics technologies
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(Microbiology & Immunology, University of Michigan) Minimum Requirements Ph.D. in applied mathematics, computational biology, quantitative biology, or a related field. Experience in ABM development and ODE/PDE
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evaluation. Automate routine data management and quality assurance processes. Utilize version control and best practices for code management and documentation. Optimize computational efficiency across research