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Award Summary 100% of home tuition fees paid and an annual stipend (living expenses) of £18,622. Overview Are you interested in developing a 3D Imaging Flow Cytometer for biomedical applications? White blood cell (WBC) analysis is crucial in medical diagnostics, disease monitoring, and...
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Tracking of Cognitive Load to Assess Human Factors During Inspections Many industries are relocating workers from hazardous environments to supervisory rooms, where they need to engage with automated systems
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Funding providers: Engineering and Physical Sciences Research Council (EPSRC) and RCNDE Subject areas: Human-Computer Interaction, Machine Learning Project start date: 1 October 2024 (Enrolment open
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Using a Large-Scale Human-In-The-Loop Bayesian Active Learning Approach (Ecstatic) The Comparative Judgment (CJ) method, which has gained traction in UK schools over the past decade, involves assessors
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from the vasculature of human kidneys. With this studentship we aim to explore three key concepts with the aim of bridging this basic research to a stronger position for clinical application: Assessing
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from the vasculature of human kidneys. With this studentship we aim to explore three key concepts with the aim of bridging this basic research to a stronger position for clinical application: Assessing
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/fees-and-funding/scholarships-research-students/project-related-phd-studentships/human-computer-interaction-ai-film-tv The anticipated start date is 1st October 2024. Candidate’s profile The candidate
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will employ multiplex, whole-section fluorescence imaging of rare, human, archival and/or donor pancreatic samples to study the phenotypic and spatial nuances of pancreatic pathology in both forms of T1D
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studentships available to accelerate its interdisciplinary research in the humanities, social sciences, and computing, maths, engineering and natural sciences. Each scholarship is fully-funded for three and a
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Funding providers: Swansea University's Faculty of Science and Engineering and No More Marking Ltd Subject areas: Human-Centred Artificial Intelligence, Optimisation, and Decision-Making Project