44 parallel-processing-bioinformatics-"DIFFER" Fellowship positions at University of Birmingham
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disciplines related to the UKRI-funded Supergen Network Plus on AI for Renewable Energy (SuperAIRE). You will also collaborate with different regional and national policymakers and stakeholders, including
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methane exchange in upland trees drawing on information derived from parallel field studies spanning a rainfall gradient in Ghana (and elsewhere) and modify empirical models of tree methane exchange
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intervention delivery and implementation in NHS settings Liaise with NHS multidisciplinary teams to support research and intervention delivery Support patient recruitment and consent processes in accordance with
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materials, in particular using low solvent or solvent free processing. This work will include detailed characterisation of these materials to understand the degradation characteristics of these materials
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materials chemistry research focussed on understanding and predicting novel wide band gap oxides, and in examining defects processes in these materials. Computational work will be performed in collaboration
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(microscopic or mechanical). The successful candidate will carry out research and manufacturing process evaluation to produce structural metallic materials. The applicant will work on a research project
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of and ability to contribute to broader management/administration processes Contribute to the planning and organising of the research programme and/or specific research project Co-ordinate own work with
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inversion of gravity gradient data, contribute to the development of data interfaces for multi-modal sensor integration, and perform advanced data processing and inference to support subsurface imaging and
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to broader management/administration processes Contribute to the planning and organising of the research programme and/or specific research project Co-ordinate own work with others to avoid conflict
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the appropriate area. Familiarity with statistical analysis software (e.g., STATA, R, SPSS) or computer programming (e.g. C++, Python, R) and experience working with health-related data will be advantageous