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of new methods and their application to investigate the organisation and dynamics of cell interfaces. As a Postdoctoral Researcher, you will also: Plan and conduct experiments, analyse and interpret
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applications (e.g. natural language processing, multivariate time-series data), to develop systems that improve the efficacy of machine learning-based technologies for healthcare applications. You must hold a
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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of the research programme is to develop EHR common data model specifications and to advance knowledge in the field of psychiatry EHR research, including clinical risk prediction modelling. The appointee will work
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. publish internationally and give lectures. apply for projects and raise third-party funds. teach courses in the master's programme "Philosophy and Economics" (within the scope of the provisions
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, computer science, statistics, or a related field together with strong programming skills in Python, R, or similar languages, and proficiency in high-performance computing. You will have experience in large-scale
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project will involve both remote-sensing and field-based observations and data collection. It will provide outputs to the World Bank CAWEP (Central Asia Water Energy Power) programme to aid the design
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including cell culture, organ-chip models, tissue engineering, and musculoskeletal biology. The PDRA will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and
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the Department of Engineering Science at the University of Oxford. The post is funded by the Oxford Martin Programme on Circular Battery Economies. It is fixed term up to December 2027. You will undertake
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from theory appropriate fluid-wall microenvironments to enable these workflows. It will also be required to develop programs and workflows to maintain cell culture for extended periods of months