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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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annotations are scarce or unreliable. Recently developed unsupervised learning methods allow to circumvent this limitation by learning patterns in unlabelled medical images and then leveraging them
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Deadline: 21 August 2025 Details Project type: Academic-Led project Supervisors: Dr Ning Ma and Professor Jon Barker, University of Sheffield Project Partner: Yorkshire Ambulance Service NHS Trust Your PhD
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researchers working together to develop better understanding of decision-making processes in the provision of active travel infrastructure. The project will address research questions such as, why are some
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The Ethox Centre is an internationally recognised multidisciplinary bioethics research centre at the University of Oxford. It is located within the Nuffield Department of Population Health. Ethox is
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, covering all cardiac conditions. This makes them unsuitable for identifying rare or complex cases, where annotations are scarce or unreliable. Recently developed unsupervised learning methods allow
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dispersion - and develop a system to disperse the particles. The project will explore the options for dispersion and the options for nozzle design and whether substantial additional air supply is needed
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, prospective project developers are faced with technological risks concerning safety such as gas cross over within stacks, and performance such as efficiency decrease due to degradation, and inability to operate
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requires not only quantification of respective changes in materials but also development of novel tools for design and optimisation of new engineering solutions. This will be achieved by combining
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it is possible to tune the FTU by changing the nozzle size, it may not be practical or economically feasible to expect manufacturers to develop nozzles of various sizes to enable facile dosing