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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process
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“Decoding faba bean yield stability: From in-field image data to mechanistic models (DIGIFABA)”, which is financed by Novo Nordisk Fonden. Start date is (expected to be) 1 October 2025, or as soon as possible
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injection, ion transfer, and structural dynamics in realistic and model systems for battery materials. The position will span experimental efforts at large scale X-ray facilities, handling and reduction
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focus on charge injection, ion transfer, and structural dynamics in realistic and model systems for battery materials. The position will span experimental efforts at large scale X-ray facilities, handling
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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process
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tasks will be to: Develop and implement machine learning models for dynamic simulations of renewable power systems Develop comprehensive guidelines for verifying and testing dynamic equivalents Integrate
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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