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an original programme of research working with ecologists Dr Ashley Lyons and Dr Anne Oxbrough in collaboration with Dr Steven Ewing at the RSPB Centre for Conservation Science. This PhD is part of the Cumbria
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position initially and is expected to be held full time and in person. You will join the CNNP Lab, which is well supported with recent funding of over £3M. The lab is based in the School of Computing
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Rolls-Royce University Technology Centre (UTC) in Manufacturing and On-Wing Technology Applicants are invited to undertake a fully funded three-year PhD programme in partnership with industry
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Tandem Industry-Academy funded project https://www.vaikuttavuussaatio.fi/en/funded-projects/tandem-industry-academia-tia-seed-2024/ . developing next-generation optical computing technologies for ultra
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uncertainty quantification for robust structural design, particularly for complex aero-engine systems with limited experimental data. Recent work by the University of Southampton developed a novel data driven
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categories for a better capability of managing the uncertainty related to system complexity and data availability to achieve more accurate RUL estimations The student will have the opportunity to work with
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-processing crucial. However, video restoration and enhancement are complex due to information loss and the lack of ground truth data. This project addresses these issues innovatively. We propose using prior
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generating coherent text, mimicking human-like conversations, and completing complex language tasks such as translation and summarization. However, despite their powerful generative capabilities, these models
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combination of academic and industrial challenges which will enhance the student’s ability to tackle complex intellectual and practical aspects of computer vision and robotics. We are seeking talented
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to the development of multiscale computational models for simulating crack propagation and establishing reliable methods to predict the residual strength of composite structures. The simulations, performed in Ansys