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submitting a cover letter explaining how your experience aligns with the role, your CV, and contact information for two referees. Only applications received before midday on the closing date will be considered
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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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earthquake engineering problems, preferably with a focus on liquefaction of sands. Informal enquiries may be addressed to Prof. Orestis Adamidis (email: orestis.adamidis@eng.ox.ac.uk) For more information
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. Letter of reference If you want a referee to upload a letter of reference on your behalf, please state the referee’s contact information when you submit your application. We strongly recommend that you
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work on the PANGEA-HIV project, analysing viral sequence data to assess how effective broadly neutralising antibodies may be against current HIV strains in Southern Africa. Second, you'll support early
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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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models to study direct interaction between macrophages and other tissue resident cells. Additionally, you will test hypotheses and analyse scientific data from a variety of sources, reviewing and refining
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Postdoctoral Research Assistant in Design for Behaviour Change: Circular Economy for Medical Devices
important real-world problems through rigorous and ambitious academic inquiry. Informal enquiries may be addressed to Prof. Lucia Corsini (email: lucia.corsini@eng.ox.ac.uk) For more information about working
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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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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