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for candidates with a background in meteorology, climatology, physics, engineering and any related discipline, and a strong interest in applying advanced physical and computational methods to real-world
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PhD Studentship: Artificial Intelligence for Building Performance – Optimising Low-Pressure Airtightness Testing Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo
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Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo (School of Computer Science) External Partner: Build Test Solutions Ltd (BTS) Start Date: 1st October 2025
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requires not only quantification of respective changes in materials but also development of novel tools for design and optimisation of new engineering solutions. This will be achieved by combining
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; gender diversity in Science, Technology, Engineering and Mathematics (STEM) through our Athena SWAN Bronze award and action plan, we are members of the Women’s Engineering Society (WES) and Working
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challenges in quantum technology adoption stem from the lack of standardized benchmarking methods and the inherent difficulty in validating quantum devices beyond classical simulation capabilities. Recent
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new. Applicants should have (or expect to obtain by the start date) at least a good 2.1 degree (and preferably a Masters degree) in Engineering or Physical Sciences. Applicants should be able
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engineering, food engineering, mechanical engineering, or related discipline. Good team working, observational and communication skills are essential with the ability to work independently and as a member of a
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An opportunity to apply for a funded full-time PhD in the College of Arts, Technology and Environment, UWE Bristol. Ref 2526-OCT-CATE-02 The expected start date of this studentship is 01 October
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well as academically new. Applicants should have (or expect to obtain by the start date) at least a good 2.1 degree (and preferably a Masters degree) in Engineering or Physical Sciences. Applicants should be able