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of repeatedly solving wave equations. In the project, we will develop a new mathematical and computational framework that combines PDE-based modelling with ideas from data-driven reduced-order modelling. The aim
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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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project. Computational mechanics PhD projects PhD 1: Rolling contact fatigue in green bearing steels – numerical microstructural modelling [SKF; Ron Peerlings] PhD 2: Predictive analysis of edge crack
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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
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will be combined with theoretical modelling, statistical data analysis, and numerical simulations to identify the governing mechanisms and to determine whether and how proximity to a phase transition
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made large-scale models available to the public, which enables the integration of AI in everyday objects and tasks. As a result, the model scale is doubling yearly, causing a proportional increase in the
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the experimental lab (https://www.mathbioleiden.nl/software.html#virtualleaf ). Incorporate detailed insights into the model of the mechanical properties of cell walls based on experiments and small-scale
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, and how strain rate influences material behaviour. The resulting experimental data will be used to validate numerical models and contribute to certification by analysis of future composite structures
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will work with researchers in environmental geo-spatial AI method development, soil modelling and spatial statistics. Where to apply Website https://www.academictransfer.com/en/jobs/362722/phd-position
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and melt inclusions (MI) in volcanics from various plume localities and will use that data in geochemical and geophysical numerical modelling. The team will work on three main tasks: Improve