530 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UNIV" "UNIV" PhD positions in United Kingdom
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wide range of social science methods. Key commercial sectors include (but are not limited to) data centres and high-tech industries, as well as food and beverage production. This project is a
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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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The minimum entry requirement is 2:1 (any degree with a substantial biological sciences component). Mode of study Full-time Start date 1 October 2026 Additional Funding Information This project is fully funded
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: The funds for this post are available until 31 December 2028 in the first instance. To apply online for this vacancy and to view further information about the role, please click the 'Apply' button above
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progression Sector-leading salary and remuneration package (including 39 days off a year and generous pension schemes). Further Information We are hoping that the successful candidate will start their contract
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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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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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geotechnics/soil mechanics. The following desirable skills are an advantage, but not a requirement. Data analysis skills in python An interest in energy policy / the economics of energy Numerical modelling