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Predicting infiltrative glioblastoma progression using advanced magnetic resonance imaging methods Project Supervisors: Michael Chappell, Steffi Thust Project Overview Glioblastoma (GBM) is the most
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at the tumour margin represent a key target for earlier and more effective therapeutic intervention. This PhD project will develop advanced MRI analysis methods and imaging-driven predictive models focusing
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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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to molecular indicators alone. We have now at our disposal a novel nanometer resolution 3D correlative imaging pipeline that combines light and X-rays and allows us to utilise the cellular landscape as a useful
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a set confidence level, typically 90% probability of detection. This project aims to take a radically different approach and integrate the array images with structural integrity assessment to predict
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are seeking a Ph.D. student to join our multidisciplinary team developing a radical solution for better detection and treatment that uses ultra-thin snake-like robots and advanced optical imaging techniques
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Novel optics and AI approaches to image the centre of a live root for the first time. This exciting opportunity is based within the thriving Optics and Photonics Research Group in Faculty
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are required for applications such as in energy storage. The participating research groups have experience in thermal processes, laser imaging techniques and novel materials synthesis and the successful
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The PhD studentship will broadly explore development of cutting-edge AI solutions for image registration, anatomy segmentation, and immersive technology. The selected candidate will work with preoperative
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computer vision method for medical image analysis principally in oncology or pathology, with a possible focus on generative AI, explainability, multi-modality. Candidate’s profile A good Bachelors degree