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socioeconomic inequality. DIVREP involves three broad objectives: (1) assembling data on childbearing age and fertility levels, and estimating novel indicators of variation in reproduction for over 120 countries
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longitudinally collected sequencing datasets (both Illumina and Oxford Nanopore) of clinical isolates that can be linked to electronic healthcare record data and/or metagenomic data. These unique datasets provide
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. This will involve analyzing sequence data from bacterial isolates collected during a clinical trial combined and from large scale lab evolution experiments. The postholder will work as part of a large team
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Natalia Ares (email: natalia.ares@eng.ox.ac.uk) For more information about working at the Department, see www.eng.ox.ac.uk/about/work-with-us/ Only applications received before midday on the 14th October
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model and data biases; (2) build and evaluate XAI tools for external auditing and red-teaming; (3) generate predictive explanations without accessing model internal; (4) providing insight into model
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statistical and computational methods designed to use “big data” and to address questions of direct or indirect relevance to common complex diseases and disorders. The appointee will join the group of Professor
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oriented environment. The post holder must have experience with EEG and should be able to carry out acquisition and analysis of EEG data independently. The post holder must also have a strong statistical
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) prior to taking up the appointment. The research requires experience in continuous-wave and pulse ESR spectroscopy, including experimental setup, setup optimisation and coding for data analysis and
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Oxford’s Department of Orthopaedics (NDORMS) as well as collaborators in Bristol and Cardiff. You should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely
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communities bordering the West Nile, Lake Albert, and Lake Victoria. To be considered for the role, you should hold (or be close to completion of) a PhD/DPhil in Health Data Science, along with relevant