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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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transport phenomena. Scientific Background Numerical simulation of turbulent flows always involves a trade-off between accuracy and computational cost. Depending on the objectives, different modeling
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fluctuations. Next, controlled time-dependent signals and benchmark optical information-processing operations will be used to compare performance at different distances from the phase transition. Experiments
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: Completed, or soon-to-be completed MSc in the biological sciences or different fields in the natural sciences (e.g. computational, mathematical, earth or marine sciences) with a strong interest in ecology and
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systems, or continuous-time and discrete-time LTI systems theory is a plus. Experience with mathematical modeling, optimization, numerical computation, algorithm development, or machine learning. Prior
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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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on ocean and coastal dynamics, marine processes, and their response to environmental change through a combination of field observations, data analysis, and numerical modelling. The position is embedded
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experimental backgrounds. Regular scientific meetings will help coordinate the different approaches within the project, compare experimental results with physical models, and promote interactions among team
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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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adaptation to antimicrobial drugs. The specific focus is on the influence of mutation rates for resistance against different antimicrobials and associated evolutionary trade-offs, such as collateral