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well as Civil and Structural Engineering and 27th for Environmental Sciences in the QS World University Rankings by Subject 2025. BEEE is one of the constituent departments of the Faculty of Construction and
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on previous research at Cranfield, which has demonstrated the benefits, the project investigates the impact of various porous structures on aerodynamic performance. Focus is placed on the entire incompressible
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. The resulting dataset will be analysed using Structural Equation Modelling (SEM) to quantify the relationships between these factors and uncover both direct and indirect pathways affecting behaviours
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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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holistic views of complex chemical and biological systems. However, discrepancies in data structure, measurement scales, and resolution across platforms make this integration challenging. Existing approaches
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alongside numerical simulations relying on high-performance computing and reduced order modelling. We aim to gain new insights about the physical coherent structures which are most relevant to viscoelastic
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studentship focused on developing a next-generation α+ß titanium alloy for aerospace applications. This industry-linked project, in collaboration with Rolls-Royce plc, will be based within the Structural
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
this, you will work with emerging AI techniques such as large language models, which can interpret technical documentation, and knowledge graphs, which help structure and connect engineering knowledge
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to structure your proposal as appropriate for your project, but you should ensure that the following areas are covered: (a) background and rationale; (b) proposed methods (including consideration of ethics and
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, whose modular nature suggests limitless variability in their structure and chemistry. In a multidisciplinary research project involving the University of Manchester, Oak Ridge National Laboratory and IBM