163 web-programmer-developer-"LIST" "https:" "https:" "https:" "https:" Postdoctoral positions at University of Oxford in United Kingdom
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and career development of our postdocs and research staff. To help them thrive and achieve their ambitions, we have created a comprehensive range of opportunities and initiatives designed to provide
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development of our postdocs and research staff. To help them thrive and achieve their ambitions, we have created a comprehensive range of opportunities and initiatives designed to provide an exceptional
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-term for 4 months. This position combines two complementary research directions at the forefront of quantum technologies: 1) the development of high-fidelity, scalable control systems for solid-state
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Chemicals PLC and the University of Oxford. The postholder will undertake the synthesis and characterisation of functional polypropylenes, contributing to the development of materials for advanced, high-value
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properties of the f-elements, with a particular focus on developing systems for imaging applications. You will manage your own research activities, including planning and executing experimental work, analysing
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is 12.00 midday on 10 April 2026. Interviews will be held as soon as possible thereafter. At the Dunn School we are committed to supporting the professional and career development of our postdocs and
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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