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temperature within the engine environment. The aim of the proposed research is to develop modern primary atomisation models which better capture the atomisation physics associated with modern aerospace airblast
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
graphs, and ontologies, the research will help engineers transform unstructured maintenance records into explainable insights. By capturing both technical and experience-based (tacit) knowledge, the system
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REACTOR DESIGNS FOR THE SUSTAINABLE PRODUCTION OF LIGNIN-DERIVED END-PRODUCTS VIA DEPOLYMERISATION REACTIONS This exciting opportunity is based within the Advanced Materials Research Group
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Funding Source: EPSRC DLA Interdisciplinary Scholarships Stipend: UKRI rate stipend for 3.5 years full-time (70 months part-time). Full Payment of academic fees (home only) A Researcher Training
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implementation of decentralised personal data governance frameworks? Technology: How can multimodal knowledge graphs in combination with generative AI help individuals govern their data (e.g. within decentralised
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-disciplinary input where appropriate. Applicants are encouraged to highlight specific areas of interest in their cover letter to help us identify suitable supervisory arrangements. Research Training Environment
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at the internationally recognised IVHM Centre, the research is supported by collaborations with Boeing, Rolls-Royce, Thales, and UKRI, offering a unique environment for cutting-edge work in fault-tolerant hardware
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motivated applicant to undertake an original and applied programme of research on the development of community-led approaches to mental wellbeing in Wigan as part of Edge Hill University’s Civic Agreement
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academics at the University of Vienna thrive on continuous exploration and curiosity and help us better understand our world. Does this sound like you? Then join our accomplished team! Your personal sphere
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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM