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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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simple identification of nuclear material even when the typical signatures of the materials may be unavailable. X-ray imaging is commonly used to image concealed objects but x-rays are attenuated in
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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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. The project will investigate how advanced and modern cryptographic protocols, such as zero-knowledge proofs, secure multiparty computation, homomorphic encryption, exotic signatures, and their post-quantum
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The research in this doctoral opportunity will investigate the relationship between material elastic and thermal properties by using high resolution digital imaging under dynamic loads. Digital
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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
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A competition-funded PhD studentship is available in the School of Chemistry at the University of Birmingham to develop and apply nuclear magnetic resonance spectroscopy and imaging to advance
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supporting international policy goals for deep-sea biodiversity protection. Research methodology This project will combine seafloor visual survey, targeted sampling and AI-assisted image analyses to: Define
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operators in a cycle of designing bespoke, inflexible models. Large Language Models (LLMs) represent a paradigm shift, offering a path to a more sustainable and intelligent approach. Their emergent
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that coordinate many clients via regional aggregators, including federated learning steps that let homes benefit from each other’s patterns without exposing local data. 3) Prototype and validate in practice. Deploy