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science, computer vision, medical/image analysis is essential. Experience of research (or interest in) in one or more of the following: deep learning; big data management; computational pathology; medical imaging
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will also be an integral member of the large, multidisciplinary BuildZero project team, and will contribute to wider project tasks, events, and outputs. Further information can be found at https
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Rethinking scholarly and editorial practices for born-digital data Digital Humanities Institute PhD Research Project Self Funded Dr Isabella Magni Application Deadline: Applications accepted all
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healthcare technology. Project Overview Healthcare digital twins are virtual replicas that continuously assimilate patient data to provide personalised predictions and support clinical decisions. To enable
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limited to machine learning, Natural Language Processing, large language models, data visualisations, and linked open data, can help streamline and improve editorial workflows. At the same time, it
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general, can you decide interesting properties of your input by examining only a tiny part of it? In this era of big data and information explosion, reading the entire input is prohibitively costly
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, and spray-on electronics, working with several industrial collaborators, including Tata Steel, Rolls-Royce and the National Nuclear Laboratory. The candidate will benefit from working within a large
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low carbon district heating as a key strategy to enable large scale decarbonisation building sector, to achieve net zero by 2050. Currently, 2- 3% of heat demand in the UK is covered by district heating
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and GTC/HiPERCAM and NTT/ULTRACAM high-speed photometric data for a large number of magnetic white dwarf binaries. You will be responsible for developing new methods for analysing these objects, with
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. Cyber-physical power systems deploy the latest information and communications technologies to enable the data and information flows across different entitles of physical networks. Such ‘cyber’ systems