74 proof-checking-postdoc-computer-science-logic Postdoctoral positions at Duke University in postdoctoral
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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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for patients. Applicants will be considered for an exciting newly funded NIH RO1 project. Areas of interest include LRRK2 biology, Rab phosphorylation (pRabs), lysosomal and endosomal trafficking
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through excellence in education, research, and clinical practice. With more than 1,500 students, we offer a comprehensive range of programs, including the Master of Nursing (MN), Master of Science in
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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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, Computational Biology, or a related scientific discipline, or expected completion before the start date. Demonstrated research productivity through first-author publications, submitted manuscripts, or comparable
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motivated individual with experience in deep learning and a PhD in computer science, electrical engineering, biomedical engineering, biomedical informatics, biostatistics or a related discipline. Required
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Department of Cell Biology is seeking a Postdoctoral Associate position to join a project in the lab of Debby Silver. The Silver lab at Duke University School of Medicine seeks a highly motivated fully funded
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of the approaches we use, that’s just fine! Our lab is a training environment; we are primarily interested in recruiting people who love science and are willing to put in the work to achieve their goals. DEFINITION
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contributions to biomedical science. Be Bold. Join a research program focused on uncovering the cellular, molecular, and neural mechanisms underlying migraine and chronic pain. You'll leverage cutting-edge
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. This position is designed for scientists with strong computational and quantitative training who are interested in agent-based modeling, network science, infectious disease dynamics, uncertainty quantification