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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 components are in use
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parameters based on paired visible-light and X-ray images. The developed techniques will be validated on real data. As a candidate, you must have a strong background in machine learning and computer vision, as
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sanctions throughout their lives. This project proposes a paradigm shift: rather than viewing sanctions as standalone events, we aim to examine their effects across the life course. Are you interested in
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Mathematics (Inverse Problems), Computer Science (Machine Learning, Computer Vision, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of