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2024, Nature) and will integrate modelling methane exchange in upland trees with the LPJ-GUESS dynamic global vegetation model to identify past, current and future changes in this new-found methane sink
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remission as a model of flare vs remission with a 50% relapse rate. Initial data analysis has taken place using the 10x Chromium single cell sequencing identifying putative cellular subpopulations
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in statistics, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded
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of fungal pathogens. The successful candidate will make extensive use of a range of in vivo models of fungal infection and will have access to the wide range of transgenic tools and in vivo immunology
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of fungal pathogens. The successful candidate will make extensive use of a range of in vivo models of fungal infection and will have access to the wide range of transgenic tools and in vivo immunology
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guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration arising from research Contribute to Departmental
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provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration arising from research Contribute
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interpretation. This role will involve working closely with civil engineers, computational modellers, Physicists, and geophysicists to translate raw sensor outputs into actionable insights. Role Summary Lead data
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funding scheme, supporting new collaborative opportunities. Promotes equality and values diversity acting as a role model and fostering an inclusive working culture. Research and Dissemination: Propose
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relation to subject area To contribute to the induction and direction of other research staff and students as requested Contribute to developing new models, techniques and methods Undertake management