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Field
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Aerial Vehicles (UAV), e.g. drones, are increasingly used for equipment anomaly and fault detection in offshore wind turbines. When the drones are employed to take images, the quality of the images can be
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have the opportunity to develop their computational modelling capabilities in this project, alongside learning new skills such as testing on biological tissues and medical image processing
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through the University’s Apply to Newcastle Portal In ‘Course choice’ tab, put ‘Postgraduate Research’ in 'Type of Study', ‘Full Time’ in ‘Mode of Study’, ‘2025’ in ‘Year of Entry’, code ‘8440F’ in ‘Course
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processing techniques that take full advantage of these capabilities, in order to translate them into optimal radar performance. The purpose of the PhD is to lay down theoretical and practical foundations
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due to a high Stoke’s shift, and a fast response time. In this project we will develop prototype perovskite scintillator gamma detectors fabricated from perovskite materials grown at Surrey. Perovskite
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imaging and monitoring of resin infusion in sample composite structures to build the digital twin and then explore methods for defect prediction and real time process control. The improved process
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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results from human decision-making to inform the design of this new paradigm, and feed the results of the latter back into human decision-making to help make it more explainable. The PhD student will: (1
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discovery, and deep-learning algorithms • Neutron scattering and advanced characterisation techniques The successful candidate will work closely with other PhDs and postdocs involved in similar investigations
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will be imaged across different field and thermal histories using MFM, magneto-optical Kerr effect (MOKE) imaging, and synchrotron-based X-ray magnetic circular dichroism (XMCD). In parallel, electrical