39 modeling-and-simulation-post-doc Postdoctoral research jobs at University of Washington
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, the candidate will have the opportunity to engage in research using advanced immunologic techniques, including mouse and xenograft models, transgene delivery and/or gene editing, immunologic assays, and single
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, multi-color flow cytometry, mouse disease models, human patient samples, 3D bone marrow organoid models, single-cell RNA-Sequencing, and general molecular and cellular biology techniques. Working
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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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(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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organoid culture, genetically engineered murine models, and human samples. The lab has successfully competed for various funding. The appointment is viewed as a training or transitional period preparatory to
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. Computational and bioinformatic skills. Experience in microscopy. Generation and analysis of mouse models. Handling of human samples. Molecular biology skills including CRISPR, cloning and qPCR. In vitro cell
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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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, 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
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their degree in the near future) in Cancer Biology or a related field. Proficiency in experimental techniques such as cell/organoid culture, library construction, imaging and handling animal models. Experience
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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