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algorithms for large-scale or distributed training/Robustness, fairness, and personalization in multi-agent learning/Training efficiency and communication reduction/Distributed training of transformer models
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), mathematical evolutionary modeling (game theory, dynamical systems, agent-based simulations or other), bespoke probabilistic modeling / (Bayesian) data analysis (e.g., in the Rational Speech Act framework
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holistic multi-hazard risk framework capturing cascading effects across systems and scales; (2) the creation of digital environments utilizing real-time data for dynamic risk evaluation; (3) the advancement
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separately, yet a reliable, open-source tool integrating a shallow-water solver and a multiphase porous-media solver within the same framework is missing. Without this coupling, it is not possible to predict
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project “Single cell multi-omics to unravel niche plasticity in AML therapy resistance“ we are looking for a PhD student. The project is part of the SFB/CRC 1709 “Cellular Plasticity in Myeloid Malignancies
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“Research for a life without cancer" is our mission at the German Cancer Research Center. We investigate how cancer develops, identify cancer risk factors and look for new cancer prevention
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Kohlenforschung, Mülheim/Ruhr Ruhr University Bochum University Duisburg-Essen Teaching language English Languages The doctoral programme is conducted entirely in English. Full-time / part-time full-time Programme
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and