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changes. In this role, you will take a lead on developing data analysis approaches and contribute to the overall study design and implementation. In particular, this will involve applying existing or even
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; testing hypotheses and analyzing data from a variety of sources, reviewing and refining working hypotheses as appropriate; engage with industrial stakeholders to understand needs and disseminate results
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Postdoctoral Researcher in Digital Pandemic Preparedness. The post holder will manage and carry out research in digital pandemic preparedness by leveraging multiple types of personal digital and real-world data
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and realign how we measure and model populations by infusing new types of data, methods and unconventional approaches to tackle the most challenging demographic problems of our time. We are seeking a
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on academic research that relies extensively on survey data and work with interview data, historical case studies, cross-national and sub-national data, and the literature related to this programme of research
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with relevant experience, and possess demonstrable experience of generating bulk and/or single-cell resolution RNA sequencing data from fresh and archival or fixed tissue samples. You will have documented
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on process development, electrode manufacture and performance assessment, but depending on the skills of the successful applicant, may also involve some aspects of modelling or data science. The post is funded
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: keith.channon@cardiov.ox.ac.uk For more information about working at the Department, see https://www.rdm.ox.ac.uk/ Only online applications received before midday on June 26th will be considered. You will be
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to Prof. Dong (Lilly) Liu (email: dong.liu@eng.ox.ac.uk) For more information about working at the Department, see www.eng.ox.ac.uk/about/work-with-us/ Only online applications received before midday on 4th
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associated with the research group of Professor Christopher Yau based in the Big Data Institute at the University of Oxford. The role will involve developing novel artificial intelligence (AI)-based methods