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Partnership Your qualifications: PhD in environmental / agricultural science, (rural) sociology, human geography, political sciences, or related subjects Knowledge of transdisciplinary approaches and methods in
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understanding and knowledge of climate dynamics. The candidate should have experience of statistical (multivariate) concepts and should be open to apply new and upcoming AI methods to analyze the climate
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
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independent work but demands a comprehensive understanding and knowledge of climate dynamics. The candidate should have experience of statistical (multivariate) concepts and should be open to apply new and
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
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, probabilistic models Representation learning, self-supervised learning, foundation models Data analysis, non-linear statistics, knowledge management Your profile PhD in Computer Science, Bioinformatics
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smart grid). While there has been tremendous progress in formal verification of cyber-physical systems, existing approaches still require expert knowledge. The main goal of this project is to develop
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The Leibniz-Institut für Wissensmedien (IWM) conducts research into the acquisition and sharing of knowledge and cooperation with digital media. The institute is a member of the Leibniz Association
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; knowledge in numerical methods and simulation, particularly for partial differential equations, and basic knowledge in mathematical modeling with/and PDEs, with a focus on fluid or biomechanics, porous media
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innovation and serves the needs of the economy and citizens. Researchers from the fields of economics, law, and political science collaborate at SAFE. Within the European project ESG UPTAKE aimed to strengthen