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Field
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distributed quantum computing. The center includes other quantum faculty, and conducts a wide range of collaborative quantum research in the areas of quantum computing, quantum algorithms and complexity
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Learning ” within the research group “Data Mining and Machine Learning ” at the Faculty of Computer Science, led by Prof. Tschiatschek, develops methods of machine learning and artificial intelligence
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standard track (30 months at IMT Atlantique + 3 months at University of Waterloo, Canada where the PhD student will stay 3 months at Prof. Ricardez’ lab. + 3 months at a non-academic partner). 1.1 Domain and
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; (d) Participation in testing and validation activities in an operational environment (testbed in a real water distribution network); (d) Production of technical documentation and contribution
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Machine Learning ” within the research group “ Data Mining and Machine Learning ” at the Faculty of Computer Science, led by Prof. Tschiatschek, develops methods of machine learning and artificial
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into embedded prototypes to demonstrate real-world feasibility. The overarching goal is to bridge high-level algorithmic innovation with energy-aware hardware deployment, enabling intelligent sensor systems
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probability distribution known only up to a normalization constant, is fundamental in Computational science, engineering, and Bayesian statistics. Recent research suggests that gradient flow-based algorithms in
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Machine Learning ” within the research group “Data Mining and Machine Learning ” at the Faculty of Computer Science, led by Prof. Tschiatschek, develops methods of machine learning and artificial
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ETH Zurich | Space and the Gravitational Physics Research group led by Prof. Michele Vallisneri in the Dept. of Physics at ETH Zurich invite applications for a Software Engineer position (for one
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of distributed computing, machine learning, image and text analysis, randomized data structures, high-performance computing, and quantum algorithms. Beyond this research, we aim to support computational thinking