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experience in cell/vascular biology and small animal disease models. Preferred Qualifications Previous experience in flow cytometry, CyTOF, RNA-seq, and/or small animal disease models (preference in models
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Job Description Position Summary Postdoctoral position is available in the lab of Dr. David Wang focused on RNA bacteriophage biology. RNA bacteriophages have been largely ignored by the scientific
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culturing, manipulation through genetic approaches, microscopy, flow cytometry, molecular biology, functional cell-based in vitro assays, and in vivo modeling of infection in both mouse and rabbit models
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publishing data in research journals. Provide supervision and guidance to laboratory staff and trainees. Required Qualifications Ph.D. in Cancer Biology or related field. Preferred Qualifications Research
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Postdoctoral Research Associate (Genomics, Data Integration, Deep Learning, AI) - Radiation Oncology
an ambitious interest in developing tools and applying cutting-edge bioinformatic and deep learning/AI techniques to advance our understanding of cancer biology and treatment. Our agile, growing
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discovery of Orsay virus, the first and to date only virus that naturally infects C. elegans (Felix et al, PLoS Biology 2011). By forward and reverse genetic screening, we have identified multiple genes
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to target human cancers. Research background and experience in molecular biology, biochemistry, genetics, cell biology or a related research field is preferred. We offer an inspiring, intellectual
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expected to work on mouse models with a group of highly motivated young scientists to employ interdisciplinary approaches, such as retinal cell biology, functional genomics, imaging, and biochemistry
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injury models, and molecular biology techniques using proximal tubule cells in vitro to investigate tubular responses to injury. Experience with these techniques is not required, but highly motivated
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Scholar that will be enthusiastic about collaborative, cooperative, and interdisciplinary research. Research experience in experimental mouse models, immunology, flow cytometry, cell biology, molecular