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imbalanced data dominated by good samples, with many defect types underrepresented. Labeling such datasets is inefficient, as most labeled data will be defect-free, and training models on these imbalanced
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labs in Flanders and leading companies in pharma, chemicals and consumer goods. Within this project, your focus is on keeping AI models trustworthy over time and minimizing (re)labeling effort. The
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. Diverse inputs, such as product images, OCR text, label images, manuals, and web documents, are to be structured and validated within a product data backbone that supports reuse, repair, refurbishing
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interest in one or more CCM areas of research and/or comparative economic law. Capability to become part of the existing research group in Brussels and Leuven, and to complete a PhD within 4 years. We offer
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in total). You will be part of a close-knit team led by prof. Yves Stevens. You will work in a team of researchers who are affiliated with other Flemish universities. We are commited to high-quality
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to complications in about one-third of adult patients. You will be part of a project that uses both animal models and patient data to develop a better understanding of the changes in blood and lymphatic vessels
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independently and as part of a team. You are willing to actively contribute within CiTiP (e.g. by setting up internal collaborations, participating in social activities, etc.). Knowledge of empirical research
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cobalt are crucial components of lithium-ion batteries and are essential for the production of smartphones and electric cars. Although there are enormous ion resources hidden in the ocean and to be
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, combining street-level information, citizen-generated data, and spatial analyses to assess how visible, accessible and equitably distributed different kinds of green spaces are. A key part of your work will
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associated development process, as well as disease-relevant validation tools and clinical insights. As part of the project, the PhD candidate is expected to apply for a competitive personal fellowship (e.g