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honours degree in materials science, physics, engineering, or a related discipline. The ideal candidate will be self-motivated, with an interest in both computational modelling and practical manufacturing
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’. Use ‘Course Search’ to identify your programme of study: · search for the ‘Course Title’ using the programme code: 8040F · Research Area: Civil Engineering · select ‘PhD Civil
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-informed data analytics tools for the predictive maintenance (PdM) strategy applications to high-value critical assets. Among others, the recently developed Physics-informed Neural Network (PINN) technique
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, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of social and networking opportunities. How to apply
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critical to ensuring the longevity and safety of fusion reactors. This PhD project focuses on developing an integrated framework that combines cutting-edge computational models, including Monte Carlo
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evaluation. Prognostics is an essential part of condition-based maintenance (CBM), described as predicting the remaining useful life (RUL) of a system. It is also a key technology for an integrated vehicle
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programme (transferable skills training), provide those studying a research degree with a wealth of social and networking opportunities. How to apply For further information please contact: Name: Dr Jelena
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EPSRC iCASE PhD studentship with SLB - Computational modelling of advanced geothermal systems School of Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded UK Students
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biology, chemistry, psychology and social science, facilitating knowledge discovery. The intuitively uninterpretable high-dimensional data and network data become visually scrutable upon being mapped into 2
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Applicants should have a first or second class UK honours degree or equivalent in in Design, Engineering, Computer Science/IT or a related subject. Experience in system design, and/or manufacturing is