142 web-programmer-developer-"https:" "https:" "https:" "https:" "https:" "Newcastle University" Postdoctoral positions at University of Oxford
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The Oxford Sustainable Law Programme (SLP) is a world-leading multidisciplinary research centre operating at the intersection of law and sustainability. Founded by Thom Wetzer , the SLP is a joint
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. The post-holder will be one of six centre-funded postdoctoral researchers delivering on projects that form our core research programme. They will be a cornerstone of the centre, collaborating across our
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literacy and managing online behaviours over the past two decades. We are looking for an individual who is interested in carrying out the project’s research programme under the supervision of Dr Ekaterina
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We are seeking a talented and motivated researcher to join the Mead Group to contribute to a major research programme focused on understanding and preventing disease progression in
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Pathology group. You will be part of a bigger EU-funded project which goal is to develop a safe and efficient cell therapy based on genome edited T cells for IgA nephropathy (IgAN). IgAN is the most common
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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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, 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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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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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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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