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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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represent dynamical systems, how their stability and robustness can be characterized, and how controllers can be designed for them. Your work will combine rigorous theory, numerical methods, and applications
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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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, enabling more efficient downstream metallurgical processing and improved metal circularity. Over recent decades, numerous sensing technologies have been developed for metal scrap characterization. Yet
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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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structure-preserving methods for mathematical models of physical systems, including topics such as geometric numerical integration, finite-volume and finite-element methods, variational formulations
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methods, image processing, high-speed imaging, cryogenic testing, composites, numerical modelling or non-destructive testing is an advantage. You can work independently while collaborating effectively with
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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
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to space-related technologies, and implement their solutions as cutting-edge, efficient numerical methods. The focus is on building rigorous frameworks that can capture the complexity of challenging
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modeling, construction of numerical methods, coding, testing, numerical simulations, and possibly measurements. You will mainly do your programming work in a mixed programming environment, i.e. combining