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. Postdoctoral Associate - Multi-agentic Coordination, Self-learning and AI Safety in Health Be You. The Department of Surgery at Duke University Medical Center seeks a Postdoctoral Fellow to lead research in
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sparse-regression based techniques to derive interpretable and computationally efficient differential equation models from computationally intensive multi-cellular agent based models (ABMs) of Epstein–Barr
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comparable records of research activity, which remains the property of Duke University upon termination Adherence to University standards regarding use of isotopes, chemicals, infectious agents, animals, human
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, infectious agents, animals, human subjects, and other regulated materials. Open, regular, and timely communication with the mentor regarding all aspects of the Postdoctoral Appointee’s research activities
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University upon termination Adherence to University standards regarding use of isotopes, chemicals, infectious agents, animals, human subjects, and the like Open and timely discussion with the mentor regarding
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) and their relationships with neighboring tissues in pathophysiological conditions. We utilize in vivo mouse genetics, live imaging, 3D organoids, genome-wide Cas9/Crispr based functional genetic
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standards regarding use of isotopes, chemicals, infectious agents, animals, human subjects, and the like. Choose Duke. Duke Surgery is #1 in NIH Grant Funding. We are an internationally recognized leader in
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evidence-based guidance that advances equitable ocean governance and positive social-ecological coastal outcomes. Despite increased attention to equity in research and ocean policy, inequitable ocean
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for genomics (e.g., generative models, transformers, agentic workflows) and/or statistical learning (e.g., network & spatiotemporal modeling, functional/longitudinal data, time-series). Analyze single-cell
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Medical Human Gross Anatomy (including neuroanatomy) as well as other anatomically-based medical school courses at an advanced and clinical level. Candidates will also be involved in new curriculum