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, you will have the opportunity to advance scientific expertise on integrated modelling of the entire water cycle, with particular focus on real-time simulations and operational forecasting. A key element
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and behavioural experimentation. Key research tasks include: Developing learning-based behavioural models of navigation, route choice and adaptation; Applying reinforcement learning, probabilistic
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degree in computer science, mathematics, statistics, physics or relevant fields. Strong background in machine learning, preferably experience in probabilistic modeling, Bayesian machine learning, or graph
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detection to identify and characterise deviations from normal system operation in a principled, probabilistic manner. Your competencies We are looking for a motivated candidate with: A Master's degree in
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of Sciences (UCAS), integrated into the MOE Social Science Laboratory of Digital Economic Forecasts and Policy Simulation led by Professor Ying Liu. There is an active group of PhD students and postdocs working