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Field
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data collection and management Data analysis and model building Develop advanced deep learning and machine learning algorithms. Assist with organizing large-scale multimodal neuroimaging dataset, brain
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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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spanning multiple locations and entities, where complex constraints and resource interdependencies – among people, machines, and robots – demand the deployment of intelligent algorithms for orchestration
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learning on large-scale HPC systems Scalable and energy-efficient AI training algorithms Image reconstruction, segmentation, and spatiotemporal modeling High-performance computing for large-scale AI and
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on creating innovative artificial intelligence algorithms for the trusted visualization of large-scale 3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems
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, 2022) and extended this to the triple equivalence between neural dynamics, Bayesian inference, and algorithmic computation (Commun Phys, 2025). -We validated it within in vitro neural networks (Nature
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researcher in algorithmic game theory and/or online learning, working with Prof. Celli at BIDSA and the Department of Computing Sciences. The project studies how multiple machine learning algorithms interact
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trigger reconstruction architectures for future particle collider experiments, based on deep learning models distributed across multiple hardware processing stages. The mission of this position, based
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will have the opportunity to engage in pioneering research, collaborate with a large, dynamic and multidisciplinary team, and advance the field of quantum computing through innovative algorithms and
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. Essential Duties and Responsibilities Neuroimaging data collection and management Data analysis and model building Develop advanced deep learning and machine learning algorithms. Assist with organizing large