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Statistics is opening a PhD position in mathematics focusing on the analysis of Partial Differential Equations. The position covers four years of third-cycle studies, including participation in research and
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solid knowledge of and show interest in mathematical analysis, partial differential equations and related subjects and is expected to have completed related courses. Documented knowledge in kinetic theory
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in statistical analysis, quantitative methods, or mathematical modelling obtained outside these subject areas may also be included. The requirements do not need to be fulfilled at the time of
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a focus on topological data analysis, to a wide range of application driven questions. A primary interest is developing reliable methods based on rigid mathematical foundations targeting visualization
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at least 30 credits must be at the advanced (master's) level. Courses in statistical analysis, quantitative methods, or mathematical modelling obtained outside these subject areas may also be included
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experience that will strengthen your application: Operating filters or reactors Molecular biology techniques Programming, data analysis, and statistics Mathematical modelling Wastewater engineering Contract
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aluminium through AI-driven microstructural analysis. About us The PhD candidate will work at the Division of Data Science and AI , in the neuro-symbolic research group. This group works with combinations
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: Mathematics, Mathematical Statistics and Computational Mathematics. The research at the Division of Computational Mathematics covers many different areas in numerical analysis, symbolic computations
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. The research group led by Martin Enge is specialized in methodology-driven analysis of patient data, especially in the field of single-cell multiomics. We are a multidisciplinary group with expertise in both dry
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consist of the following: Mathematical analysis of ecological and eco-evolutionary models, involving pencil-and-paper calculations; Computer simulations of more complex models which do not easily lend