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also develop resource models by compiling relevant datasets and applying data science tools. The Postdoctoral Associate should be able to work effectively with collaborators from diverse disciplinary
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the non-human primate (NHP) model by exploring innovative mRNA constructs for immunogen delivery that can elicit both protective and therapeutic B and T cell responses. Recently, Dr. Williams was also
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cancer, or related field Preferred Qualifications: Experience working with mammalian cell culture and animal models of cancer (xenografts and GEMMs) Familiarity with next-generation sequencing platforms
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the mechanisms of, and interventions for, immuno-senescence and aging in lung transplantation using high-throughput multi-‘omic approaches, primary cell culture systems, and animal models of transplantation. Ph.D
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biology, immunology, or other relevant areas of biomedical sciences. Experience in one or more of the following areas is desirable: 1) In vivo mouse models (willingness to work with animal models is a must
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application to quantum theory and information science. Other application areas of interest include robust parameter estimation and performance bounds under model misspecification, integrated sensing and
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, neuroinflammation, tau and α-synuclein pathobiology, digital pathology/AI image analysis, and mouse models of neurodegeneration. Education: A recent Ph.D. (less than 2 years of postdoctoral experience is strongly
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. The Sarantopoulos Lab is seeking a B-cell enthusiast. We are using primary patient samples and mouse models to understand the role of B cells in anti-leukemia/tumor responses. For over a decade, the lab
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focusing the complex interactions between human host factors (genetic traits, health status, etc.) and environmental exposures (especially air pollution) in order to understand how risk factors affect human
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researchers and physicians work together to solve important clinical problems. The current and prior work of our team includes the development and evaluation of foundation models as well as deep learning