38 phd-mathematical-modelling-ecological-modelling Postdoctoral positions at University of Washington
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methods to advanced imaging techniques. Currently, a number of mathematical models exist to describe the onset and progression of Alzheimer's Disease and the effects of anti-amyloid therapies on disease
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experience in molecular and cellular neurobiology to study neuronal regeneration and preservation in retinal mouse models of injury and disease. This project will examine how cellular metabolism impacts
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, to define novel biomarkers, and to identify novel therapeutical targets. We have pioneered in the integration of genetics with omic data to identify proteomic signatures and develop novel predictive models
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encouraged to apply: Biologists with mathematical, computational, or programming experience. Prior experience with mouse models, motivated to learn new techniques including advanced optical imaging
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Position Summary The Ornitz Lab at WashU Medicine is seeking a highly motivated postdoctoral researcher with experience working with mouse models of development and disease. Candidates will have the
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(including Crohn’s disease and ulcerative colitis) using molecular and cell biology, multi-omics technologies, murine models, and human tissues. We currently have three major focuses: 1) Innate lymphoid cells
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multidisciplinary approach, spanning basic biology and translational medicine using mouse models and patient samples, tackles complex questions with profound implications for human health. Projects are available
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, cell sorting, next-generation sequencing, CRISPR/Cas9 screens, and mouse and iPSC stem cell models. We welcome applicants from multidisciplinary scientific backgrounds, including neuroimmunology, tumor
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metrics since 2000. 2. Assess the Effects of 3-D Urban Structure on Extreme Humid Heat: Analyze variations in humid heat using Landsat thermal bands, MODIS, and humidity data, modeling how urbanization
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, single-cell multiomics, tissue engineering, and animal models. Our current research primarily focuses on four key areas: 1) Developing robust, chemically defined differentiation protocols to generate