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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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band score of at least 6.5, internet. TOEFL test (TOEFL-iBT) showing a score of at least 90, or a Cambridge CAE-C (CPE). For additional information, please contact Prof. Dr. Erik Koffijberg
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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 this project
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group has implemented state-of-the-art deep learning for underwater communications; deep learning models underwater environment based on real data. Our preliminary study shows that state-of-the-art deep
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are looking for a highly motivated and skilled PhD researcher to work on graph-based machine learning surrogates of wind energy systems. Our goal is to accelerate flexible fatigue load estimation
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to data-driven research projects focused on glaucoma, diabetes or nAMD using large-scale clinical and imaging datasets. Develop, validate, and implement machine learning models and statistical tools
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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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algorithms are used that allow a computer to process large data-sets and learn patterns and behaviours, thus allowing them to respond when the same patterns are seen in new data. This include 'supervised
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PhD Scholarship in Big Data and Analytics for Crop Genetics Modern agriculture and biomedical research are driven by the availability of big data and the development of data science. The recent