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Field
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, Mathematics or Computer Science (or a related field) with an emphasis on applied mathematics/statistics/machine-learning. Prior experience in the probabilistic machine-learning, neural-networks, statistical
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the fellowship will be hosted by the Department of Mathematical Sciences (https://www.ntnu.edu/imf ). The project is a close collaboration with evolutionary ecologists from the Department of Biology
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wireless communication systems and standards. Our research spans fundamental theory, algorithm design, system-level analysis, and practical implementations for 6G and beyond wireless technologies. We work
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systems for use in breaking waves, both in the field and in the lab Contribute to analysis of images, and development of the open-source analysis software PyOPIA (https://github.com/SINTEF/pyopia
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optical engineering: Imaging and image analysis, optical engineering, detector development, microscopy, X-ray optics • Structural Biology and Mechanical Engineering: Automation, high-precision mechanics
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basic physics. The researcher will perform theoretical and laboratory work to develop optimum methods for measuring the mass of the particles, including radionuclide samples. Advanced uncertainty analysis
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of reactor transients and quantify how surrogate uncertainties propagate through system safety analysis of nuclear installations, using tools such as open simulations platforms. This research will be part of a
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of Mathematical Sciences and active research themes see: http://www.nottingham.ac.uk/mathematics/index.aspx . To find out more about the People and Culture in the School of Mathematical Sciences please visit our
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exchange and professional development in an interdisciplinary environment through annual symposia, workshops, and retreats, as well as monthly seminars. Further information is available at: https://www.uni
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will develop hands-on experience in plant physiology, nutritional assessment, disease severity evaluation, transcriptomic and metabolomic analysis, and scientific data interpretation. You will also gain