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consumption while guaranteeing optimal power production. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop graph-based
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for optimizing metals microstructures in-situ during the AM process as well as ex-situ during post-AM treatments and enable predictions of the microstructural evolution, and thus changes in properties, while AM
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techniques that optimize both aspects. The candidate will perform the work together with a team of postdoctoral researchers who are experts on the field and other PhD student working in the topic. In general
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of these materials.State-of-the-art characterization techniques such as DSC, DMA, DTMA, micro-Computed Tomography (micro-CT), optical microscopy and Scanning Electron Microscopy (SEM) are combined with advanced numerical
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with privacy by developing techniques that optimize both aspects. The candidate will perform the work together with a team of postdoctoral researchers who are experts on the field and other PhD student
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advertisement About the position A Doctoral Research Fellowship is available at the Faculty of Computer Science, Engineering and Economics at Østfold University College. This PhD candidate will play a central
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for optimizing metals microstructures in-situ during the AM process as well as ex-situ during post-AM treatments and enable predictions of the microstructural evolution, and thus changes in properties, while AM
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learning. The project involves a collaborative team, including a postdoctoral researcher and a PhD student, with specific objectives: Define and acquire a comprehensive database of high-quality video priors
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for wind turbines, with the ultimate objective of including structural health information in windfarm asset management to optimise structural lifetime consumption while guaranteeing optimal power production
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Course location Stuttgart Description/content The Graduate School of SimTech offers an interdisciplinary structure and international training programme in order to prepare the candidates with