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relaxations of the underlying PDE constraints can effectively reduce the nonlinearity of the inverse problem. Understanding this requires mathematical analysis of the PDEs and the resulting inverse problems, as
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whether suitable relaxations of the underlying PDE constraints can effectively reduce the nonlinearity of the inverse problem. Understanding this requires mathematical analysis of the PDEs and the resulting
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systems. The mathematical disciplines involved are mathematical modeling, numerical analysis, and scientific computing. Your tasks will involve: Conducting research on uncertainty quantification in
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resources efficiently. In this PhD project, you will develop mathematical theory and computational methods for the analysis and design of chaotic sampling mechanisms in networked control systems. You will
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vision, numerical analysis and computing as well as probability and statistics. What you bring Master’s degree in mathematics or equivalent, including a solid background in analysis, dynamical systems, and
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will be employed and tested on actual measurement data as a benchmark. The project will involve mathematical modeling, construction of numerical methods, coding, testing, numerical simulations, and
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degree in applied numerical mathematics, computational/theoretical physics, theoretical biology, computer science, or a related discipline; Written and oral proficiency in English, strong scientific
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that generalize across different physical settings. Building on this motivation, the project focuses on the definition, development, and analysis of scientific foundation models: large-scale, generalizable models
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scientific writing, bifurcation analysis or numerical ocean modeling are considered a plus. Our offer A temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a
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methods that extend current sets of flood scenarios derived from physical and numerical models, incorporate climate change effects, and then use these enriched datasets to assess the future insurability of