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-driven methods provide excellent performance under low or cyclo-stationary regimes but struggle with highly dynamic and rapidly varying conditions; conversely, model-based state observers ensure robustness
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, nonlinear dynamical systems, robotics, and formal methods to develop principled models and algorithms for distributed decision-making in complex and uncertain environments. Your research The candidate will
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Overview Are you a STEM graduate with a thirst for knowledge and a talent for picking up new skills quickly? Do you thrive on a mix of simulation and modelling work, hands-on experimental testing
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position. Good knowledge of combinatorial optimization (scheduling problems, mathematical modelling etc.), machine learning and/or strong programming skills are an asset.• You have an interest in supply
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Statistics, Biostatistics, Computer Science, Data Science, Information Science, or a closely related field (completed by start date). Demonstrated research experience in statistical/mathematical foundations
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Bilevel programming (BP) is a powerful mathematical framework for modeling hierarchical decision-making processes involving two players: a leader and a follower. In energy network design, for example
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This doctoral position is part of GRAIL (“Gamma Radiation from the Atmosphere for Investigation and Learning”), a prestigious Horizon Europe Marie Skłodowska-Curie Actions Doctoral Network (MSCA-DN): https
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into this type of research: actual nerve biopsies from patients with Charcot-Marie-Tooth neuropathy due to YARS1 mutations, along with matching iPSC-derived motor neurons and Drosophila models. Now, we
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related issues, we offer a working environment in which diversity is lived. Flexibility: We demonstrate flexibility not only with the various working time models but also through the offers