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, traditional planning often fails to capture workload variability, uncertainty, and the complex interaction between product features, labor availability, and machine capacity. Your PhD will address
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quantitative methodological skills in handling detailed spatial data, including various econometric techniques and machine learning approaches; a thorough understanding of empirical, explanatory research; a
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Description This PhD position explores how AI agents can play games to generate meaningful gameplay data. You will work on reinforcement learning, automated feature engineering, and the comparison of AI- and
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description We are seeking a highly motivated PhD candidate to join
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description We are seeking a highly motivated PhD candidate to join
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bringing together a diverse team of PhD candidates who will focus on three key areas: Probabilistic and differentiable algorithms for machine learning; Programming language implementation for high
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candidate in the exciting area of multiscale and multiphysics modelling of sustainable fibrous composites, with additional focus on uncertainty quantification and machine learning. Information The context
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physical). Solid background in programming and experience with machine learning. Knowledge of participatory design and co-creation methodologies. Ability to learn independently and passion for research
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and scalable. Design and build a technology demonstrator prototype of clinical-testing grade. Collaborate with interdisciplinary teams, including clinicians, engineers, and machine learning (ML) and
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, particularly integer programming, e.g., vehicle routing and packing problems and heuristics; simulation; data-driven modelling; decision support systems; AI (reinforcement learning, machine learning). Motivation