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to develop new AI-assistive technology for detecting congenital heart conditions (CHDs) from fetal heart ultrasound scans. The Oxford team, in partnership with 5 hospitals sites, has curated a large fetal
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Associate to build a research program to tackle these key issues, reporting directly to Professor David Edwards. The successful candidate will work with large datasets, including leveraging large-scale global
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by Professor Tonia Vincent. The successful candidate will contribute to STEpUP OA, a large international Consortium focused on understanding the biological mechanisms underlying osteoarthritis
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FTE role supporting the international FEVER II study. C-GULL is a large contemporary birth cohort following up to 3-4,000 infants. Nested within C-GULL, HBHF is investigating early predictors of anxiety
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bioinformatics and spatial analysis techniques to large-scale spatial transcriptomics and imaging datasets, using tools such as MuSpAn to identify spatial biomarkers and uncover the biological mechanisms driving
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working with human date and experience analysing large-scale omics datasets (e.g., proteomics, transcriptomics, genomics, metabolomics, or related high-dimensional biological data) are desirable
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, deployment and evolution of AI agents. By establishing foundations for trustworthy agent engineering, FRAME will enable productivity, adaptability, self-improvement, reliability and foster large-scale adoption
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for better training and novel network designs. Low Effective-dimensional Learning Models. We will extend foundational theory of how large ML systems can be regularised to have dramatically fewer trainable
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/opportunity-spaces/resilient-climate-and-ecosystems/accelerated-adaptation for more information on ARIA and this programme). The project is a collaboration between groups at the Universities of York and Exeter
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optimization of large language models (LLMs) and related architectures for generative tasks, continuous learning, indexing or retrieval, support of retrieval augmented generation over many data points from long