28 experimental-fluid-mechanics Postdoctoral positions at Duke University in United States
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MD or PhD or equivalent degree and has interests in immunotherapy and/or hematopoietic stem cell transplantation using mouse animal models. The research involves understanding the mechanisms underlying
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scientist eager to contribute to one or more of our ongoing research themes: 1. Plant community response to climate change 2. Mechanisms of biodiversity maintenance 3. Biodiversity-climate feedbacks 4
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alone ––without a deep understanding of Ecology or Evolutionary Biology would in principle not be enough for this position. Fluency in data analysis in R, and strong experimental skills are essential
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Bioinformatics expertise required for scRNAseq analysis. · Previous cell culture experience. · Perform molecular, cellular, biochemical and immunological analyses. · Optimize and troubleshoot experimental
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: Lead innovative projects investigating molecular, cellular, and circuit mechanisms of ion channels and lipid transporters in neurological disorders. Participate in a range of research activities
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Duke University, Mechanical Engineering and Materials Science Position ID: Duke -MEMS -PDAQUINO [#30494] Position Title: Position Type: Postdoctoral Position Location: Durham, North Carolina 27701
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University is looking to hire a postdoctoral researcher to contribute to our studies on the molecular and biomechanical mechanisms of cell sheet morphogenesis during dorsal closure in the model system
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journal clubs. · Assist in figure preparation for manuscripts and presentations · Maintain a scientific record of any experimental plans and processes performed · Perform other related duties incidental
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chemoproteomics, chemical biology, and related areas. The interested candidate will work directly with experimental scientists within a wet lab setting to facilitate the management, analysis, and visualization
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models that include these mechanisms. The postdoc will develop biologically-constrained machine learning–based model discovery pipelines to derive interpretable surrogate ODE/PDE models from simulated ABM