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, Algebraic Geometry, Combinatorics, Data Science, Number Theory, Probability, and Quantum Computing. Fellows have previously been appointed with backgrounds in most areas of Pure Mathematics and Statistics
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networks. You should have experience of building machine learning models for environmental applications. A high level of data science and computational expertise is essential, as is experience with Bayesian
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quantitative data analysis of large secondary datasets and be based at the University of Bristol. There are opportunities to work on several other ongoing and upcoming research projects to help develop your
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responsibilities may include: Collect and analyse spectrum data using JOINER-NSF, establishing key patterns and trends in spectrum utilisation and creating automated techniques for detecting and identifying specific