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well as the development of numerical methods that can eventually be applied to large-scale wave-imaging problems. The PhD project will have a strong mathematical component. You will investigate questions concerning
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Are you fascinated by application-oriented research in mathematics and eager to work at the interface of numerical optimization, optical design, and uncertainty quantification? In this PhD project
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Mathematics, Biophysics, Mechanical Engineering, Materials Science or related disciplines · A strong foundation in continuum mechanics and transport phenomena · Experience with numerical methods and finite
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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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inverse problems, as well as the development of numerical methods that can eventually be applied to large-scale wave-imaging problems. The PhD project will have a strong mathematical component. You will
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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
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? We are looking for a PhD candidate to develop AI methods that extend current sets of flood scenarios derived from physical and numerical models, incorporate climate change effects, and then use
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microstructure. An integrated numerical-experimental approach is generally adopted for this goal. A state-of-the-art computing infrastructure is in place for the numerical work in this project. PhD projects
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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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., plasticity, damage, fracture) in engineering materials at different length scales, which emerges from the physics and mechanics of the underlying multi-phase microstructure. An integrated numerical