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can lead to defects during hot press forming. Accurate prediction of such defects requires both careful experimental characterization of frictional behavior and advanced constitutive models to describe
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: Multiscale modelling to better understand RFB behavior and identify optimal hierarchical shaped pore- and electrode-structure to encounter optimum electrolyte as well as electrical flow. Prototyping
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dynamics and learning in artificial and biological neural networks, with the aim of: Unveiling the link between network structure and neural representations. Understanding the impact of structural and
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computational model to capture the complex transport of gases, liquids, and charges in these porous structures, including the complex interfaces between them. Insights from the model will directly guide the
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participation in forms of collaborative policy making. Your angle will be to investigate how features of social structure (e.g., social networks, social influence) affect the success or failure of inclusive
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Application deadline: 23 September 2025 Apply now Are you eager to advance research at the crossroads of language, AI, and geography? As a PhD candidate in the ERC-funded GeoTrAnsQData project at Utrecht
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mobility systems. In our 12 collaborative labs we apply advanced technologies such as sensing, data analytics, modelling, and AI to turn scientific research into real-world impact. You’ll join an open
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/en/jobs/354372/phd-position-spines-modelling-t… Requirements Specific Requirements Highly motivated students with a MSc in construction engineering and management, complex system engineering and
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on the mathematical theory enabling these advances, via asymptotic analysis and nonparametric modeling. You will work in the Statistics section at the Delft Institute of Applied Mathematics (DIAM
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needs to be supplied with rigorous uncertainty analysis. The focus of this project is on the mathematical theory enabling these advances, via asymptotic analysis and nonparametric modeling. You will work