432 web-programmer-developer-"https:"-"https:"-"https:"-"U.S" Postdoctoral positions in United Kingdom
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MRI (fMRI), functional Ultrasound Imaging (fUSi) and computational modelling of emotion-related behaviours. This is an exceptional opportunity to develop your research portfolio within a team of
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for Artificial Intelligence, and the Digital Futures Institute. The PDRA will also have access to research and career development from King’s Centre for Research Staff Development. The postholder will work closely
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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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traumatic intracranial haemorrhage. You will also be given the opportunity to contribute to teaching and engage with career development opportunities. The post is part-time (60% FTE) and is available for up
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for Artificial Intelligence, and the Digital Futures Institute. The PDRA will also have access to research and career development from King’s Centre for Research Staff Development. The postholder will work closely
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, Prof Alessandra Russo and other collaborators in the University of Cambridge and in Japan, within the UKRI NeSyDebates project. The work will focus on contributing to developing effective safeguards
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-chairs of strategic nurse advisory councils in London and the South East respectively). The post holder will be responsible for working with stakeholders, including experts by experience; developing
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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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are committed to support career development and encourage innovative thinking to tackle major challenges in Immunology. About the role We are seeking a highly motivated Postdoctoral Research Associate in
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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