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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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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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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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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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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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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
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samples, including aspects of sample preparation and data analysis Good presentation skills (written & oral) Qualifications of merit: Knowledge of other synchrotron X-ray/IR techniques Knowledge of lab