452 postdoc-in-thermal-network-of-the-physical-building PhD scholarships in United Kingdom
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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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performance of industrial systems (up to 100 MW+). You will receive specialist training through the Engineering Hydrogen Net Zero CDT and be based at Loughborough University. Primary supervisor Sonya Calnan is
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distribution. This process often takes place in large scale driers where the material is heated and broken up mechanically with mixing blades. However, under certain conditions the process can break down as the
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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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including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during their PhD
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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, embedded intelligence, and adaptive cyber-physical systems that operate safely under uncertainty and dynamic conditions. This PhD at Cranfield University explores the development of resilient, AI-enabled
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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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, potentially including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during
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bottleneck in the screening process. This PhD project will address this through deep integration of scanning probe electrochemistry, optical microscopy and machine vision, to develop a system that can