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and networking. They will be working within a vibrant community of research degree students and researchers at both institutes. The post-holder must have a relevant first (or postgraduate) degree in
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energy storage within HVDC networks is a promising response to these challenges. Such integration allows HVDC systems to deliver a broad range of new grid services, including fast frequency response
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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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The Child and adolescent Health Impacts of Learning Indoor environments under net zero (CHILI) Hub is a program funded by the MRC and NIHR, the goal of which is to understand the health effects we
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, including staff, students and industry partners, benefits from a close network of knowledge and opportunity exchange. Situated in Shropshire, the campus and the surrounding area provide an excellent working
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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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similar languages) Experience with large-scale neural network simulations Experience with analysing large-scale neural recordings Familiarity with neuroanatomy and neurophysiology Knowledge of dynamical
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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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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