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Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 4 hours ago
Movement Study, we are closely collaborating with Assistant Professor Xucong Zhang (Delft University of Technology) to develop systems and algorithms that allow for eye gaze study through multiple camera
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(MERCE). The main objective is to develop safe planning and reinforcement learning algorithms with various degrees of confidence for variants of Markov decision processes. More precisely, we will develop
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sampling-based and reinforcement learning-based motion planning algorithms for multiple robotic arms in automotive manufacturing, including testing, performance evaluation in both simulation and actual
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research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which
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sampling-based and reinforcement learning-based motion planning algorithms for multiple robotic arms in automotive manufacturing, including testing, performance evaluation in both simulation and actual
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Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts. Your key responsibilities will be to: design and implement mathematical algorithms, and facilitate their integration into Magma engage with
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at the University of Sydney and externally across multiple institutions publish research papers on mathematical theory and the development and analysis of algorithms compile data sets relevant to research in
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for biomolecular systems, including prediction of protein-ligand, protein-protein, and antibody-antigen structures and affinities, and protein conformational ensembles. Design active learning algorithms and
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security