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Field
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students and senior researchers from multiple disciplines to tackle challenges in sustainable aluminium through AI-driven microstructural analysis. The NEST-WISE project offers a vibrant collaborative
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technical work packages: WP1 Annoyance from wind turbines WP2 Wind turbine noise data collection and analysis WP3 Wind turbine noise source modeling WP4 Wind turbine noise propagation modeling WP5 Wind farm
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science with demonstrated experience in quantitative analysis. We are looking for a range of talents and expertise, including in machine learning, mathematics, or statistics. Experience with one of the focus
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Mathematical Sciences at the University of Göttingen as well as the associated research training group "Fourier Analysis and Spectral Theory" and the collaborative research centre "Mathematics of Experiment
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) Computer Science/ Mathematics/Physics and at the second cycle level, 60 credits in Life Science, Computer Science Mathematics, Physics or Bioinformatics including a 30 credit Degree Project (thesis). Additional
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reuse of energy systems analysis processes. In line with FAIR and Linked Open Data principles, you will design interfaces that enable the smooth processing of big data in the context of scientific, AI
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benefit from a co-supervisor based at the nearby John Innes Centre, a world-renowned centre for plant science, where you will spend time in the Biomolecular Analysis Facility. You will also have the
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to velocity profiles, which will be informative for the design of offshore renewables. Further mathematical analysis of these nonlinear terms will shed light on the question: what generates these extreme waves
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, Skills and Experience • You will have substantial technical experience in time series analysis, ideally either in neurophysiology data or wearable sensor data • You will have experience of at least
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background in addition to a good background in mathematical analysis. The project interacts with several areas of mathematics: computational harmonic analysis, approximation theory, orthogonal polynomials