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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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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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also look at other large-scale and multi-omics data. You will be looking at applications both in neurological diseases such as stroke and Alzheimer's, as well as various forms of cancer. Apart from pure
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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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longitudinal aging study, the Betula Project, as well as the UK Biobank. The candidate will handle, process, and statistically analyze large amounts of data on blood markers, cognitive tests, and health and
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on collating and analyzing the large volumes of carbon cycle data gathered from the site to date, then preparing the resulting analyses for publication in scientific journals. Likely topics for papers include
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Description of the workplace The research group includes oncologists, pathologists, and basic scientists. After more than a decade of translational studies and large-scale analyses
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, fitting to the project plan. Your profile The candidate should have a PhD degree in natural resource economics or a similar subject. Proven experience in data analysis of markets related to natural
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propagation problems, stochastic partial differential equations, geometric numerical integration, optimization, biomathematics, biostatistics, spatial modeling, Bayesian inference, high-dimensional data, large
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these systems, and all production uses energy. With large and increasing uncertainties about the future energy system in both the short and long term, the uncertainty in the analyses risks increasing. The purpose