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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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environmental control systems and other onboard systems, providing a realistic environment for research and training. SIU 737-200 ECS: A ground-based Boeing 737-200 Environmental Control System used
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the potential to transform clinical ophthalmology, offering improved diagnostic capabilities and deeper insights into the structural integrity of the retina. At a glance Application deadline03 Dec 2025 Award type
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communication skills for regular interaction with other stakeholders, with an interest in applied scientific research. Funding This fully-funded studentship is open to UK Home students only. Sponsored by EPSRC
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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical
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structure would enable you to understand science better at atomic level. You will learn the skills of presenting the results to small and large groups of people via presentations in conferences and meetings
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to human and environmental interactions across various sectors such as healthcare, education, and urban planning. The primary aim of this project is to develop Multi-Intelligence Agents (MIAs) that combine
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conferences. Cranfield operates a substantial Doctoral Researchers Core Development programme (DRCD) for its research students. This programme provides a generic structured training programme which is
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providing world-class facilities in a supportive, innovative, inclusive and interactive learning environment. Based at Cranfield University, a global leader in aerospace research, the project benefits from
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infinite extent models and limited extend data based on trust over particular sets, and naturally create explainable AI structures which can further be analysed from a verification and validation perspective