496 web-programmer-developer-"https:"-"https:"-"https:"-"UCL"-"UCL" PhD positions in United Kingdom
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linked directly to Jungbunzlauer, a leading producer of biodegradable ingredients. Jungbunzlauer products enter global markets daily, and you will be contributing to real industrial development rather than
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molecular imaging Team with access to both cutting-edge instrumentation for preclinical imaging and world-renowned expertise. Together, we are developing next-generation whole-body imaging tools for cancer
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knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of
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fees for the period of the relevant programme as outlined in the offer letter (usually three years). CSC will provide living allowances as prescribed by the Chinese Government, and will cover the round
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supply chain resilience. Following a PhD‑by‑papers route, the research aims to deliver three high‑quality scholarly outputs and develop insights to enhance supply chain management practise. This project
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performance. This PhD project aims to develop a data-driven framework for graphene aerogel design by integrating structured experimental Design of Experiments (DoE) with machine learning (ML). The student will
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early detection and predict adverse pregnancy outcomes. You will develop and validate a data-driven clinical decision support tool in collaboration with clinicians and industry partners. Pre-eclampsia is
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. Specifically, we develop small molecule photo(cyclo)addition reactions that allow for the efficient formation of covalently bound reaction products under (visible) light irradiation. Importantly, the thus formed
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this, empirical rules have been developed. However, a fundamental understanding of the process is still lacking. Furthermore, current standard tests do not adequately capture the phenomena, and thus industry is
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the noise associated with near-term quantum devices. This in turn offers an exciting new dataset from which it will be possible to use machine learning to train a more accurate functional for use in density