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. - Neural networks and machine learning strategies for the analysis of scattering data. Large amount of scattering data obtained in our group requires development of the advanced analysis techniques. In
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one of the following analysis techniques (multiple preferred): normative modelling, dimensionality reduction techniques, machine learning, deep-learning, state space modelling, advanced statistics
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for Quantum Technology (WACQT, http://wacqt.se ). The core project of the centre is to build a quantum computer based on superconducting circuits. You will be part of the Quantum Computing group in the Quantum
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, towards future colliders. Cutting-edge machine learning developments for classical and quantum computational platforms are pursued in the group to benefit particle physics and beyond. Experience Candidates
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, towards future colliders. Cutting-edge machine learning developments for classical and quantum computational platforms are pursued in the group to benefit particle physics and beyond. Experience Candidates
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Nancy and the long-standing experience in sophisticated computer simulation studies from Leipzig, promising unique prospects in advanced education of PhD students via research into this important field
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machine learning are encouraged to apply. If you wish to discuss any details of the project informally, please contact Prof Suan Hui Pu, Smart Manufacturing and Systems Research Group, Email: suanhui.pu
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diagnosis, and knowledge of the operation of helicopter systems. • Confident handling of Python and common data science tools. • Knowledge of high-performance computing and machine learning. • Fluency in
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tools. * Familiarity with tensorflow and/or pytorch. * Demonstrated ability to design and implement machine learning techniques and algorithms. * Demonstrated expertise in the Linux computing environment
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they bond in materials, but also develop transferable skills in scientific computing, data analysis and visualisation. "Machine learning for atomic-scale structure determination in thick nanostructures" (with