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full postgraduate research programme Please note that existing postgraduate research students cannot be considered for this funding. Tenable period 3.5 years full-time or 7 years part-time. Continuation
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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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parenting and domestic violence. Evidence-based parenting interventions have become increasingly widespread in the last twenty years but are primarily used in Early Help and broader children’s services, and
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the PhD student in high-performance computing, computer programming, applied mathematics, fluid mechanics, mathematical modelling and data analysis for large datasets -of the order of 100 Terabytes
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to rehabilitation, potentially via randomized controlled trials. The project will: Establish robust testing protocols for the plantar flexors, knee flexors and extensors, and hip extensors. Explore associations
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computational mechanics or multiphysics modeling, with particular interest in fracture mechanics and chemo-mechanical degradation. Knowledge of solid-state defect chemistry (advantageous). You will join a dynamic
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use +3.5 - covering the full PhD Politics programme Please note that existing postgraduate research students cannot be considered for this funding. Tenable period 3.5 years full-time or 7 years part
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computing and analysis of data will enable the development of control mechanisms that will overcome one of the major barriers for exploiting the benefits of hybrid propellant propulsion systems. The project
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for the industry. Join us in making a difference! Mycotoxins are toxic secondary metabolites produced by various fungi that contaminate food crops, posing significant risks to human and animal health. Among
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Deadline: 31 August 2025 A fully funded 3.5 year PhD position is available to work on the project titled “Scalable benchmarking for digital quantum computers based on blind testing”. This position