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, engineering, or a related field. Strong programming skills and experience in machine learning or statistical modelling are essential. Experience with healthcare data, algorithmic fairness, or deep learning
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collaboration with colleagues in the John Radcliffe Hospital and the Oxford Big Data Institute, with the central aim being the development of rapid diagnostics of antimicrobial resistance in clinical samples. You
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the John Radcliffe Hospital and the Oxford Big Data Institute, with the central aim being the development of rapid diagnostics of antimicrobial resistance in clinical samples. You will work as a member of an
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) a PhD in a quantitative discipline such as computer science, mathematics, statistics, engineering, or a related field. Strong programming skills and experience in machine learning or statistical
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skills. Aware of the ethical issues around working with Big Data. Desirable criteria Experience applying advanced statistical or machine learning methods to complex datasets. Evidence of involvement in
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lead analyses of large-scale datasets, applying advanced computational and statistical methods to integrate multimodal data (including MRI, MEG, EEG, and genomic data). The postholder will work with a
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lead analyses of large-scale datasets, applying advanced computational and statistical methods to integrate multimodal data (including MRI, MEG, EEG, and genomic data). The postholder will work with a
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data assets, and in the context of the world’s largest longitudinal population studies, many hosted here at the Big Data Institute, as well as other international initiatives. To be considered, you must
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skills (e.g. Python, Julia) to merge concepts of chemical engineering, operations research and computer science, as you may also need to deploy machine learning to support data analytics and complex
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to reconstruct subsurface defects; Implement image/signal‑processing or machine‑learning pipelines for automated flaw characterisation; Collaborate with the Federal University of Rio de Janeiro, including short