63 science-"https:"-"https:"-"https:"-"https:"-"https:" Postdoctoral positions at Duke University
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multidisciplinary translational neuro-oncology research program focused on immunotherapy, biomarker discovery, and spatial biology. In this role, you will help advance innovative research embedded within investigator
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critical role in advancing innovative vision research through artificial intelligence, data science, and interdisciplinary collaboration. Working alongside clinicians, researchers, statisticians, fellows
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research in engineering and science related to critical minerals. This position will contribute to building interdisciplinary excellence and research pathways in critical minerals research at Duke University
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Position Description Be You. Be Bold. Choose Duke. Postdoctoral Associate Human-AI Research Pipeline (HARP) | Duke University Department/Unit: Social Science Research Institute Anticipated Start
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on implementation science approaches, to guide implementation, evaluation, and continuous learning. Lead and conduct analyses that generate actionable insights for policy, program improvement, implementation, and
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proteostasis, cytoskeletal dynamics, and ferroptotic cell death. This collaborative work combines biochemistry, chemical biology, cell signaling, live-cell imaging, and organotypic brain slice models to dissect
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, Biostatistics, Public Health, Population Health Sciences, Health Services Research, Data Science, Cancer Prevention/Control, Quantitative Social Science, or a closely related field. Strong understanding
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. or equivalent doctorate (e.g. Sc.D., M.D., D.V.M.) Preferred Qualifications:. A PhD or MD/PhD (or equivalent) in biological sciences Strong research background in cell biology, molecular biology, mouse models
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to understanding the fundamental mechanisms that drive cancer development, treatment response, and therapeutic resistance. By combining cutting-edge molecular biology, functional genomics, and translational research
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, molecular biology, tumor immunology, therapeutic resistance, or functional model systems are strongly encouraged to apply. Prior experience in epigenetics, genomics, or computational biology is a plus. This