138 web-programmer-developer "https:" "https:" "https:" "https:" "https:" "Newcastle University" Postdoctoral positions at University of Oxford in United Kingdom
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Colorectal Cancer - Stratification of Therapies through Adaptive Responses (CRC-STARS) programme, developing and applying cutting-edge mathematical methods to spatial transcriptomics imaging data in order to
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the EEE value chain. The PDRA will be responsible for working with industry partners to develop and evaluate product and system-level design solutions to enable effective reuse, repair and remanufacture
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group at meetings. • You will also have a strong publication record in a related field, and possess sufficient specialist knowledge in the discipline to work within established research programmes
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, machine learning, and/or computational biology to be able to work within established research programmes. They will have excellent communication skills, including the ability to write for publication
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absorption analyses of photocatalyst function, including operando photoinduced absorption studies, and their correlation of materials structure, spectroelectrochemical analyses and hydrogen evolution
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shares and inheritance statistics in developing and developed countries. This is a fixed term role which will end by the end of February 2027. About you You will hold, or be close to completion of, a PhD
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funding. You will be responsible for the development of novel acquisition, reconstruction, image analysis and/or modelling methods for cerebrovascular magnetic resonance imaging (MRI) to improve
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. The project will utilize and further develop upon state-of-the-art computational modelling techniques to predict excited state properties of complex materials, including but not limited to their quasiparticle
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to develop new ideas and build upon existing research within the group. The position is fixed term until 31st March 2027 in the first instance. This post could suit those wishing to prepare for a clinical
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. The successful candidate will contribute to this emerging field of AI-driven X-ray experimental science through the development of novel X-ray spectroscopic imaging experimental modalities, the design and