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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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CFD methods DFT and Molecular modelling linked to CCUS Strong analytical and problem-solving skills, with an ability to interpret and analyze simulation and/or experimental results. Ability to work in
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success and publication history, with an MD, PhD or MD/PhD degrees, and very strong references. We are seeking a candidate with expertise in immunology. Previous experience in cancer research, molecular
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integrates 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
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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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. 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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, using molecular/cell biology, immunology, and animal models. A candidate will work with a collaborative interdisciplinary team and an enthusiastic mentor. Highly motivated individuals holding a Ph.D
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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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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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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