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. “Towards Cultivating Decentralised Data Privacy, Interoperability and Trust with Semantic PETs and Visualisations”. In: NXDG: NeXt-Generation Data Governance, SEMANTiCs 2024, 17-19 Sep 2024, Amsterdam
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providing a structured, semantic framework that enhances knowledge sharing and data reuse across different platforms and systems. Project Aim This PhD will develop an ontology-based methodology to improve
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
unstructured maintenance records using LLMs, ontologies, and knowledge graphs. Build a standards-aligned semantic framework for interoperability and scalability. Model degradation over time using temporal
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your formal application, please name Prof Peter Munro as your proposed supervisor and include Project Code 24001. Contact: For informal inquiries please contact Prof Peter Munro who will be happy
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
a standards-aligned semantic framework to ensure interoperability, reusability, and scalability across systems and sectors •Model system degradation over time by developing temporal knowledge graphs
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approach is a method that is both formally rigorous and practically efficient for the verification/validation of quantum devices. Candidate’s profile Knowledge of quantum computing and an understanding
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@nottingham.ac.uk Suitable applicants will be interviewed, and if successful, invited to make a formal application. View All Vacancies
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/ . If this initial application is successful, we will invite you to formally apply. All candidates must fulfil the University of Warwick entry criteria and obtain an unconditional offer before commencing enrolment
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@nottingham.ac.uk Suitable applicants will be interviewed, and if successful, invited to make a formal application.
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems