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of Emmanuel Katsanis, MD to pursue studies in transplant and tumor immunology. Research involves murine bone marrow and peripheral blood stem cell transplantation and tumor models. Studies may also include use
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, Skills, and Abilities: Background in Salmonella pathogenesis and molecular genetic and biochemical methods. Experience with in vitro and infection models Responsibilities Research: Performing basic
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this hydrogen generation model with the ammonia synthesis module. Find out more about the Hayward research and group at: https://www.chem.ox.ac.uk/people/mike-hayward. About you Applicants must hold a
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). We are seeking a highly motivated researcher to join our team. We use a wide range of molecular, cellular, transcriptomic, and advanced imaging techniques, in combination with ex vivo and in vivo
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. The Lab uses mouse models to investigate the functional organization of the gustatory and trigeminal nervous systems. Our studies aim to delineate molecular and neural circuit mechanisms that underlie
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novel, lab-generated mouse models, and available human patient samples, the lab identifies and validates novel targets in obesity and MASLD and subsequently develops pharmacological tools that ameliorate
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2025. We seek to recruit a Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based
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models with a group of highly motivated scientists to employ interdisciplinary approaches such as retinal cell biology, functional genomics, imaging, and biochemistry. The Chen Lab has a well-recognized
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Postdoc position: mechanisms of autoimmunity & autoinflammation in inborn errors of immunity (m/f/d)
of the immune dysregulation and clinical translation. The Boztug lab is focusing on the discovery of inborn errors of immunity (IEI) and the dissection of their underlying molecular pathomechanisms. The ultimate
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hundreds of samples from multiple independent marine transmissible cancer clones. The role provides an exciting opportunity to combine single-cell cancer genomics with molecular cytogenetics and statistical