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for Biomarker Discovery: Develop and fine-tune machine learning algorithms for biomarker discovery, cancer classification, and exploring omics features. Collaborative Research: Work in a multidisciplinary setting
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generative AI algorithms and translate them into intuitive explanations. Interest in cyber-physical systems (CPS) and eco-cognition modeling. Good understanding of mathematical optimization techniques
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or PyTorch. Interest in explainable AI and contributing to explainability repositories for trustworthy, auditable algorithms. Experience or interest in cyber-physical systems (CPS), eco-cognition, and
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trajectories of individuals and households with a migration background in Belgium, focusing on hazard and microsimulation models of demographic events in multiple life domains. You contribute to the development
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of photosensitizers in electrochemistry. Moreover, it will have a potential impact in novel biosensor technologies for detecting multiple biomolecules, including nucleic acids, proteins, and other clinically relevant
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for detecting multiple biomolecules, including nucleic acids, proteins, and other clinically relevant analytes. Position You prepare a doctoral thesis in the field of molecular quenching strategies