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to office, lab space, and specialist software Opportunities to attend international conferences (e.g., USA) Involvement in Cranfield’s Doctoral Network, providing training and networking across disciplines
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
amounts of maintenance and operational data, from sensor streams to technical logs, yet much of it remains unstructured, fragmented, and underused. Hidden within these records are insights that could help
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glaucoma (POAG) is the leading cause of irreversible blindness worldwide. It arises from fibrotic remodelling of the trabecular meshwork, a filter-like structure in the anterior chamber of the eye. As the
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challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
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Background Network Rail operates several telecom networks which provide connectivity for various signalling systems. Therefore, the performance of telecoms assets is integral to how the railway system operates
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mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and machine learning frameworks such as recurrent
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researcher with expertise in communication, project management, and leadership. You will build a robust national and international network and acquire advanced knowledge essential for implementing critical
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supporting the Net Zero 2050 target. This PhD project will develop an AI-enabled framework that optimizes wind turbine control and predictive maintenance. Using Deep Reinforcement Learning (DRL), the system
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The Intelli-Ingest Doctoral Network is an EU-funded Marie Skłodowska-Curie Action (MSCA) initiative is a network bringing together leading academic, clinical, and industrial partners to train a new
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Human-AI interaction. Your network and team The Aalto Engineering Psychology Group concentrates on research in human-AI interaction . Currently, research activities focus on applying research methods from