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biochemistry, genomics, molecular genetics, cell biology, and model organism systems to uncover the mechanisms by which histone mutations disrupt human development and lead to disease. Our ultimate goal is to
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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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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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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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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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, 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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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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across model systems and human cohorts. Mentor junior lab members, including graduate students and research staff, and contribute to fostering a supportive and rigorous scientific environment. Present
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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