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or international equivalent in a subject relevant to the proposed PhD project (e.g. chemical engineering, mechanical engineering, civil engineering) is our standard entry, however we place value on prior experience
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are possible, please contact Dr Guohong Tian after the deadline passes. You will need to meet the minimum entry requirements for our PhD programme . A resilient candidate with strong background in mechanical
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of Computing, Engineering and the Built Environment , the largest of the five schools at Edinburgh Napier University. With a practical focus on adding value to the social, cultural, and economic capital of
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Postgraduate Application’. Use ‘Course Search’ to identify your programme of study: · search for the ‘Course Title’ using the programme code: 8090F · select ‘PhD Mechanical Engineering (full time
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these systems are responsibly integrated into our daily lives requires a deep understanding of their operational mechanisms and societal impacts. Doctoral students of the centre will engage in
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materials for low-emission ammonia conversion. Perform both experimental investigations and computational simulations of the combustion process. The outcome of this project will demonstrate the feasibility
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: Working knowledge of MATLAB/Python and signals processing Understanding of electromagnetics Experience with CAD and mechanical design How to apply: Interested candidates should submit a full formal
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in numerate, computational, or environmental subject areas. Numerate Subject Areas include e.g.: Mathematics, Statistics, Physics, Economics, Finance, Engineering (Mechanical, Electrical, Civil, etc
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applicant must have (or be close to obtaining) a relevant PhD in Fluid Mechanics from an Engineering, Mathematics or Physics Department, a strong background in theoretical and computational fluid mechanics
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
mechanics, and artificial intelligence (AI)—specifically in the domains of non-destructive evaluation (NDE), computer vision, and machine learning. It addresses a critical challenge in the structural health