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forms part of a new interdisciplinary research project at KU Leuven that will use explainable, adaptive and multimodal human-AI interaction methods to let generative AI spark new insights and
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equity between population groups. To address these questions, the researcher will be able to apply advanced health economic methods and make use of valuable datasets that longitudinally track Belgian
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experience in design of (analog/mixed-signal) integrated circuits. hands-on experience with methods of optimization and circuit design and layout. Candidates should be motivated, independent, show critical
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above-average academic performance. Have experience with data collection and analyzing data using quantitative research methods. Have great analytical skills and are digitally savvy. Feel comfortable
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of inhalant allergens.• Comparing clinical outcomes of symptomatic treatment versus AIT in sensitized military personnel.• Validating a novel diagnostic method using S.P.A.T. as a tool to track allergen
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dimensionality reduction as well as analysis of blood proteomic data. We are looking for a student with experience in bioinformatics and relevant statistical methods using R or Python languages. Some knowledge of