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to optimization problems with possible topics covering: Variational quantum algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical
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Analytics research group at the Catalonia Institute for Energy Research (IREC) is looking for a senior researcher (R2) to join our team and contribute to the development and integration of advanced algorithms
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III of the Call for Proposals - Demonstrable experience in tasks related to multibody systems dynamics, particularly slack modelling and data fusion algorithms with computational models. - Candidates
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III of the Call for Proposals. - Demonstrable experience in tasks related to multibody systems dynamics, particularly slack modeling and data fusion algorithms with computational models. - Candidates
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Exactly: A Bayesian Approach. The project aims to address the challenges in pooling inference, by developing and implementing either exact or asymptotically exact Monte Carlo algorithms in collaboration
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ERC project FoRECAST, we aim to develop theory (e.g., new probabilistic and differential inference algorithms as well as proofs of their correctness and efficiency) and systems (e.g., high performance
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modes (e.g., HCCI) for net-zero fuels like hydrogen and ammonia. A key innovative pillar is the development of an AI-driven control strategy. Machine learning algorithms, including reinforcement learning
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interference, while ensuring energy-efficient and scalable operation. This PhD project will focus on developing machine learning algorithms to enable robust channel estimation, intelligent user association
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collaboration with the Intelligent Maintenance and Operations Systems (IMOS) Laboratory at EPFL (Prof. Olga Fink). IMOS focuses on the development of intelligent algorithms designed to improve the performance
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremen, Bremen | Germany | about 2 months ago
ecological questions. Your Tasks Develop and test novel forms of network-based feature selection for the application of ML algorithms to marine microbial eDNA and eRNA datasets, integrating a range of