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, and mathematical and computational modelling. Experience with scientific programming, quantitative analysis, or computational modelling, preferably using R, Python, C++, or comparable tools. Interest
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AI and machine learning to ecological questions. Experience with scientific programming, quantitative analysis, or computational modelling, preferably using R, Python, C++, or comparable tools
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with H 2 -potential source rocks; - acquire and process new MT and controlled-source electromagnetic (CSEM) field data in targeted areas; - perform integrated 3D modelling of MT, CSEM and gravity or
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Computational Fluid Dynamics (CFD) and Artificial Intelligence (AI) for future flexible hydropower operation. Your work assignments As a PhD student, you will conduct research at the intersection of
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about us, please visit: the Department of Biochemistry and Biophysics .. Project description Your studies in Bioinformatics will be in the project: "AI-driven Multiscale Modelling of Membrane Protein
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current project will focus on "Governmental communication and citizen crisis preparedness", combining social science theories, empirical case studies from Italy and Sweden, and computational modelling
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) You will work within the newly established Computational Materials Science group of Assistant Professor Waldemar Kaiser, part of the Theory & Modelling unit (led by Prof. Igor Zozoulenko). Our
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research environment with close supervision and interaction between experimental and computational researchers. Research group website: https://johannescairns.github.io/meg-lab/ . Description of the project
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Information Technology Are you interested in probability theory, statistics, and mathematical modelling? Would you like to develop new methods for uncertainty quantification and apply these methods to large
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“Modelling Life at the Membrane with AI” ( https://cemerai.se ) to integrate data across scales within our interdisciplinary collaborative research center. Central publications from previous projects linked