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£20,780 per year and a budget for training and research. To apply online for this vacancy and to view further information about the role, please click 'Apply' above. All applications should be made online
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£20,780 per year and a budget for training and research. All applications should be made online. Further information on eligibility and how to apply via University Applicant Portal can be found in
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atomisers. To ensure high quality measurement data, enabling meaningful correlations, measurements will be performed on a simplified prefilming geometry, with aero and hydrodynamic features representative
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protocols for electrical biasing of samples in the microscope. A key task is to process and analyse large 4D-STEM data sets and extract information about domain wall structure and dynamics. The role involves
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system using deep learning (DL). The project’s objectives include generating training data from synthetic datasets and real-world images (cadaver and actual intraoperative THR images), developing a marker
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, data analytics, and co-designed interventions. This is an exciting opportunity to contribute to applied research that informs urban policy and planning, particularly around air quality monitoring and
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-based reviews, data collection and analysis, written outputs, and the dissemination of research findings to different audiences, including through investor briefings and academic publications. We
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of the structure and use of routinely collected cancer data. In this role, the postholder will act as a liaison between the National Disease Registration Service and the Departments of Public Health
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for cardiovascular applications. You will build on our group’s expertise on Physics-Informed Machine Learning (PIML), a powerful approach that combines data-driven AI with the rigour of physical and physiological
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automated rankings. The research includes real-world validation using university admissions data and will contribute to the broader fields of AI in education and ethical decision-making. This PhD research