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, ablations), including simulator- or metamodel-generated rollouts. Implement, test, and benchmark RL methods for policy discovery (e.g., multi-agent, multi-objective, uncertainty-aware, and/or safe RL), and
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complex materials simulations. These agents will assist with setting up, executing, and optimizing electronic structure workflows, from standard ground-state Density Functional Theory (DFT) calculations
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Bayesian Networks (DBNs) for probabilistic risk modelling Scenario-based simulation for rare-event analysis You will be part of a dynamic, interdisciplinary research setting at one of Europe’s leading
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dynamic, crowded environments. As a PhD candidate, you will develop methods that combine data-driven autonomy with formal safety guarantees and validate them in real time through simulation and experimental
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candidate, you will develop methods that combine data-driven autonomy with formal safety guarantees and validate them in real time through simulation and experimental evaluation. The position is hosted
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will contribute to developing intelligent agent that supervises energy-efficient compute offloading over distributed edge and cloud. The application deadline is December 12, 2025, 2025 at 11.59 PM
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techniques and AI, engineer robust and adaptive solution systems, and address challenges related to multi-agent coordination and decision-making under uncertainty. The ideal candidate will have a strong