505 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "UNIV" "Univ" PhD scholarships in United Kingdom
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, and data-driven analysis. The project will be supported by a strong research environment with experience in concrete behaviour at elevated temperatures, constitutive modelling, and advanced numerical
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its frontier by integrating mechanistic artificial intelligence with robotic additive manufacturing systems to enable intelligent metal processing. The research will develop physics-informed and data
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be conducted beginning May. Contact for enquiries Informal enquiries may be addressed to Prof Yafa Shanneik (ys32@soas.ac.uk ). For more information: RELI-GENE: Governing Health, Family and Religion
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that deliver healthier indoor environments, lower carbon emissions, and long-term building performance. By integrating Passive House and EnerPHit principles with real building data, the research will support the
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the Faculty of Engineering, plus those housed in Plant Biosciences at the Sutton Bonnington campus. Data sets will be generated using simulated and experimental data and these will be used to train networks
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for candidates who can demonstrate strong research potential. Suitable backgrounds include, but are not limited to: Human Factors Law (particularly law and technology, medical law, or data governance) Psychology
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are emerging as promising alternatives, offering potential benefits in carbon reduction, durability, and ageing resistance. However, widespread adoption is limited by inconsistent performance data, insufficient
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should hold a Master’s degree in Economics or a related field (e.g., Finance, Psychology, Maths or Data Science), with a foundational understanding of behavioural/experimental methods and/or econometrics
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then need to provide the following information in the ‘Further Details’ section: A ‘Personal Statement’ (this is a mandatory field) - upload a document or write a statement directly in to the application
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computational design, Industry 4.0 integration, digital twins, and data-driven optimization to enhance manufacturing efficiency. Working closely with the NWCAM2 companies, this project aims to reduce waste, embed