478 engineering-computation-"https:"-"https:"-"https:"-"https:"-"https:"-"Newcastle-University" PhD positions in United Kingdom
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Field
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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experimental and computational, to understand and predict microtexture evolution during processing. The balance between experimental and computational research will depend on the profile of the successful
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with a background in chemical engineering, physics, soft matter science, computational chemistry, and/or related disciplines. Early applications are encouraged, as the position may be filled before
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engineering, digital technologies, and systems thinking. The university’s strong reputation for applied research and its focus on technological innovation ensure that this project will be well-supported, with
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emphasis on engineering realism. The ideal candidate will have: A strong background in aerodynamics, fluid mechanics, or turbomachinery Experience with RANS CFD (commercial or in-house solvers) Strong
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up to a £5k/annum research training support grant for the full duration of the 4-year programme. Metal-ligand multiple bonding is a burgeoning area for making chemically novel structural motifs
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be made online . Under programme name, select * Mechanical and Manufacturing Engineering’* Please quote the advertised reference number: * FP-LJ-MTC/26* in your application. Applications must include a
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welcome motivated students with a strong background in engineering or science, such as physics, mathematics, computer science, or related disciplines. Skills in mathematics, computational modelling
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online via the above 'Apply' button. Under Campus, please select *Loughborough* and select Programme *Mechanical and Manufacturing Engineering*. Please quote the advertised reference number ‘SF-ST-2026’ in
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computer science, mechanical engineering, or aerospace engineering. You should have programming experience applied to physics/engineering problems and/or experience with machine learning and ML. The University