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identification and machine learning. The key challenge is striking a balance between, on the one hand, modelling the physical, dynamic and nonlinear behavior of the components with sufficient physical accuracy
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candidate. You will work in a highly interdisciplinary group, at the intersection of physics, machine learning and theoretical neuroscience. Our group is focused on investigating dynamics and learning in
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: Collaborate with other PhD candidates and researchers working on the project to share insights and learn from its different sub-projects. The successful PhD candidate will be based at the Faculty of Industrial
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, disability studies, (co-)design methods, and Human-Computer Interaction (HCI). The ideal candidate is passionate about creating socially impactful inclusive co-design methods and eager to collaborate directly
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scans and use advanced data-driven methods, including artificial intelligence (AI) and machine learning to improve outcome prediction and patient stratification. deepen our understanding of the etiology
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Join us to explore the mechanics of soft matter through a unique blend of theory, hands-on experiments, and machine learning. Job description Soft matter such as polymers and hydrogels
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understood. The HUM.AI.N-ACCENT project aims to fill this gap by combining insights from cognitive psychology, neuroscience, AI engineering, human-computer interaction and social science, with lifespan
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? No Offer Description Job description Consortium This position is part of a European Doctoral Network consortium "Machine learning for integrated multi-parametric enzyme and bioprocess design", where 15
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Job description Consortium This position is part of a European Doctoral Network consortium "Machine learning for integrated multi-parametric enzyme and bioprocess design", where 15 doctoral projects
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numerical methods, as well as familiarity with concepts in complex systems, physical memories or machine learning. We strongly believe in the benefits of an inclusive and diverse research environment, and