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on aspects of fracture processes, stochastic material behavior, and the development of physics-based models that can bridge the gap between continuum mechanics descriptions and disorder-driven statistical
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our team at DTU Compute, offering a fully funded position within a dynamic and interdisciplinary research environment. The positions are part of the research project “AI-driven materials optimization
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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of software engineering techniques to ensure interoperability of their modelling and mining ecosystem. This position will run from October 2025 (or shortly after) and it has an expected duration of 24 months. A
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Job Description These days, the inner workings of molecules and materials can be probed and modelled by advanced simulation tools on modern computer architectures. However, the routine applications