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. The position will involve development of codes/models simulating the nucleation and propagation of stress corrosion cracking in samples under low cycle fatigue conditions, as well as models for linking
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conditions at realistic, field-relevant scales. Developing a practical correction model to account for energy dissipation by flexible (vs. rigid) vegetation Original research on wave-induced forces and
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mathematical foundation of machine learning models. You will be responsible for developing scientific machine learning methodologies enabling new approaches for solving machine learning problems including
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research focus will include some of the following topics: Advanced sensor fusion and multimodal AI models for robotic intercropping. Self-supervised learning will generate multimodal agricultural pre-trained
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Madsen in an international environment at DTU Chemistry. We are interested in the discovery and characterization of novel chemical reactions proceeding in water at mild conditions and with environmentally
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Foundation Models initiative . The proposed starting date is 1 September 2025 or soon thereafter. The appointment will be made for a term of three years at a competitive salary and will follow the PhD study
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. The position will involve development of codes/models simulating the nucleation and propagation of stress corrosion cracking in samples under low cycle fatigue conditions, as well as models for linking
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to mechanical forces. We work with leading international groups on modeling and also conduct simulations at DTU. Our overarching goal is to understand and predict the mechanical behavior of metals during plastic