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Field
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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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High-Energy Physics (HEP). We seek highly qualified candidates with interest and experience in ML algorithms including unsupervised techniques, time-series modeling, and clustering algorithms
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research associate position in AI for science. The Learning Systems Group seeks a postdoctoral researcher specializing in federated learning and privacy-preservation algorithms. The successful candidate will
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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 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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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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Together, these research directions seek to reimagine how buildings and cities operate—optimizing energy use, enhancing human well-being, and reducing carbon emissions at scale. We are seeking multiple
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Wearables & Healthcare Systems Theme 3 Algorithms for Privacy, Security and Provenance Theme 4 Clinical Innovation & Translation Connected medical devices are increasingly employed in the drive towards