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and/or the CAD/CAM process is a plus. I am proficient in Python and am familiar with data science and machine/deep learning toolkits. As a PhD researcher at KU Leuven, I perform research in a structured
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. This PhD project aims to investigate wind–planet interactions in systems with cool evolved stars, focusing on how stellar outflows shape planetary atmospheric structure, chemistry, and long-term evolution
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estimation, condition evaluation, and state-of-health prediction, as well as technologies for systematically building up product and process knowledge and for structuring this information in Digital Product
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(to measure structural patterns), depending on the candidate’s preference and selected case study). We are committed to participatory research practices including co-creation of outputs, interpretations, and
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are part of a sector that is highly dynamic, with a number of structuring project portfolios in Wallonia, linked to the European Green Deal, and aimed at increasing circularity and reducing the environmental
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well as documenting and communicating results in a clear and structured manner. You will manage your tasks within defined timelines, report progress regularly to the supervisors, and coordinate efficiently with other
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, such as AI-driven virtual cells (AIVC), while contributing to developing image-based biomarkers (digital pathology) and AI-based structural antibody design. For this task, a large data lake containing
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understanding vs building risk evaluation); and (iii) the costs of performing the test (including environmental costs). For more information on the project, see the EU announcement: https://cordis.europa.eu