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local gas/liquid phase conditions. Whilst direct simulations of breakup are possible, computational cost is high, restricting applications to small sections of geometry and for modest run times
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(to help achieve net zero goals) can impact on the indoor environment and have positive or negative impacts on human health. For example, action improving insulation may increase thermal comfort within a
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Lead Supervisor name: Professor Katherine Appleton, email: k.appleton@bournemouth.ac.uk Project description Aims: This project aims to use a systematic approach to design, develop and test novel
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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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(including 7 full professors) and approximately 120 PhD students and post-doctoral research fellows. The group has excellent facilities for experimental work including approximately 2500m2 of research space
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150 members, with 18 academics (including 7 full professors) and approximately 120 PhD students and post-doctoral research fellows. The group has excellent facilities for experimental work including
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of tomorrow and creating novel solutions to major global challenges. Our community is made up of 120 nationalities, 14 000 students, 400 professors and close to 5000 faculty and staff working on our dynamic
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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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by Executive Dean Professor Chris Harty, CTE brings together four schools: Architecture & Planning, Construction, Property & Surveying, Engineering & Design, and Computer Science & Digital Technologies
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Engineering, Mechanical Engineering or related subjects. Funding and Eligibility: UK only Key Information Supervisors: Professor Tony McNally