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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 4 hours ago
. * Developing computational and algorithmic approaches to understanding the neurobiological mechanism of neurodisorders. * Interact cross-functionally: work with people across the team to find creative solutions
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mechanisms from patient samples, collaborative discovery of anti-infective therapeutics, and bacterial pathogenesis. This position provides broad training to develop independent, highly motivated scientists in
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. This position offers a unique opportunity to contribute to ongoing projects on movement biomechanics, 3D printing, mixed reality, and mechanical testing and drive the future of this program through
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. Our research program is focused on neuron-glial interactions, with an emphasis on understanding cellular and molecular mechanisms by which astrocytes regulate neurovascular coupling, local metabolism
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questions in ribosome biology. Our research is centered on understanding the mechanisms of protein synthesis and translational control in health and disease. The primary focus of the lab is to elucidate how
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curious to deliver work that matters, your journey starts here! Innovation. Interdisciplinary collaboration. Complex problem solving. In Carnegie Mellon University’s Department of Mechanical Engineering
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motivated candidates for postdoctoral fellow related to chronic kidney disease. Our research program focuses on identifying mechanisms involved in the progression of chronic kidney disease. Specifically, we
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Associate will support research in the theoretical and computational mechanics of lipid membranes. This position is part of a multidisciplinary initiative focused on advancing understanding of topologically
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motivated candidates for postdoctoral fellow related to chronic kidney disease. Our research program focuses on identifying mechanisms involved in the progression of chronic kidney disease. Specifically, we
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studying deformation mechanisms in refractory alloys as via atomic-scale calculations as well as application of machine learning to materials discovery The ideal candidate will have the following