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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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description The postdoctoral project is focused on development and the exploitation of machine learning tools to accelerate the analysis of microtomography data at the MAXIV synchrotron facility. MAXIV
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responsibilities As a postdoctoral researcher in the group, you will need to perform sample preparation, data collection and analysis work as agreed during regular meetings. You will also need to participate in
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providing autonomous solutions to optimise the cost of monitoring programmes. We’re looking for a postdoctoral researcher to join this effort, combining tools from statistical learning, sparse data analysis
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experiments Documented expertise in data analysis using scripting (ideally python-based) Experience carrying out SAXS/WAXS experiments at large scale facilities Working experience with soft matter and/or
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also include technique development work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a
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experiments, molecular cloning, cell culture, and standard laboratory methods such as flow cytometry and RT-qPCR. The computational work includes, for example, the analysis of omics data and computational
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postdoctoral position in data analysis, where you will apply machine learning techniques to understand how resistance genes spread and to help detect infections caused by resistant bacteria. The position is part
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to the development of ongoing research. This will include the integration, modelling, and advanced statistical analyses of large genetic, ecological, and environmental data sets. The successful candidate is also
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techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get unprecedented medical