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Field
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will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show challenging properties of uncertainty, irregularity and
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Research Platform (SARRP) and in vivo imaging to develop image-guided radiotherapy (IGRT) strategies for liver and childhood brain cancers. A key focus of this project is hepatocellular carcinoma (HCC
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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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is expected to soon be able to diagnose diseases occurring outside the retina. OCT images can be aberrated by the eye itself and imperfect optical design. Ocular imaging with adaptive optics promises
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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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group is actively contributing to the Electric Power Innovation for a Carbon-free Society Center (EPICS ) and is closely collaborating with partners in the UK, USA, and Australia. Funding: The PhD
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THR demand in younger patients expected to increase fivefold by 2030, revision surgeries will also rise. To improve implant positioning, image-guided navigation is increasingly used in complex THR
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Ultrafast lasers drive innovations from quantum technology to medical imaging, yet controlling femtosecond pulses remains a major challenge. Metamaterials are artificial structures with
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project