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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
intelligent methods that integrate large language models (LLMs) and knowledge graphs to interpret technical documentation and structure complex engineering knowledge. The goal is to create digital twins
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management, computer science, information management and beyond. Supervisors Primary supervisor: Professor Tom Jackson Secondary supervisor: Professor Ian Hodgkinson Entry requirements At least a 2:1 honours
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identify your programme of study: · search for the ‘Course Title’ using the programme code: 8040F · Research Area: Civil Engineering · select ‘PhD Civil Engineering (full time)’ as the
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to the development of the Department’s research strength; (c) undertake teaching duties at various levels; (d) provide leadership in developing a programme, a subject discipline or a research programme, etc.; (e
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doctoral training programme dedicated to academic research in space propulsion. R2T2 PhD programmes are already underway at nine UK universities, and the programme overall is centred on the Westcott facility
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heat transfer behaviour is known to depart from standard analytical correlations. Under the combined supervision of academics in mechanical engineering and computer science, you will consider the use
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areas such as radiation detectors, computational simulation, systems engineering and experimental techniques with sources of ionising radiation are applicable. English language requirements: Applicants
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Core Development programme (DRCD) for its research students. This programme provides a generic structured training programme which is constructed to support the researcher as the PhD progresses with
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, and public engagement. The programme is designed to prepare graduates for careers in academia, industry, or clinical innovation. Key training features include enrolment in a leading UK doctoral