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Field
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learning has strong potential for computer vision, from hyperbolic image segmentation [2] to hyperbolic tree embeddings [3] and hyperbolic vision-language models [4,5]. [1] Nickel, Maximillian, and Douwe
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new types of measurements, can help us create a more complete picture of the electron wavefunction. The project relies on a combination of concepts from quantum mechanics, information theory, and
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Scoliosis (AIS). Although surgery straightens the spine, AIS is associated with poor self-image and psychological distress. This project will investigate this, developing assessment and management tools
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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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an industry partner which is developing image-based interventions to support people living with dementia. Their interactive platform presents images that serve as prompts for reminiscence, social connection and
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computing. These include computer graphics and geometry processing, computer vision and image processing, visualization and visual analytics, augmented and virtual reality, machine learning and deep learning
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and technology. Desirable (not essential): Research experience in sports medicine and technology (e.g. publication or final year project). Programming skills in MATLAB or Python. Application Procedure
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focus on the medical image processing aspect of the Birth4Cast simulator by researching and developing automated image segmentation procedures to extract the pelvic floor muscle complex and the fetal head
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well as collaborative research in the field of medical imaging. Specific research foci include the development of ultrahigh field MRI methods in terms of both acquisition parameters and processing, including software
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its dependency on the pre-fire forest structure and management practices in Fennoscandian boreal forests. Work includes e.g. developing methods to assess burn severity and fuel structure, processing