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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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flexibility. To fully unlock this potential, we need advanced tools that digitally replicate these networks and support optimized design and data-driven control strategies. As our PhD candidate, you will
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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We are looking for a talented and enthusiastic candidate for a fully funded 4-year PhD position. The PhD candidate for this project will be working at the RNA Structural Ensemble Dynamics group led
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temporarily, as needed, when needed. The goal of this project is to advance the understanding of how working memory is implemented in the human brain. To this end, the main objective is to develop a neural
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cracking resistance as compared to GI galvanized steel. Furthermore, it is unclear at this moment how these types of coatings will perform in application to the green steel. Therefore, this project is aimed
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will design, implement, and evaluate, within the framework of Design-Based Research, a professional development programme that supports STEM instructors in using AI effectively and critically in
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researchers are expected to develop scientific independence and complete research projects. PhD candidates who thrive in their research stay abreast of developments in the field, proactively communicate
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are expected to develop scientific independence and complete research projects. PhD candidates who thrive in their research stay abreast of developments in the field, proactively communicate research results
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are published in a series of compilations and monographs about the Dutch parties) is not the DNPP’s only task; it is also responsible for systematically collecting publications (digital and otherwise) by and