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of Mathematical Statistics include stochastic models, statistical theory and computational statistics, probability theory and statistical signal processing, with applications in areas such as financial mathematics
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receding-horizon counterpart in the form of stochastic and belief-space MPC for motion planning. A key focus is on how sensing and state estimation should be actively planned to enable overall optimal
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senior researchers and doctoral students. Current research areas within the Department of Mathematical Statistics include stochastic models, statistical theory and computational statistics, probability
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assessment criteria: Experience with developing and maintaining large numerical models. Experience and knowledge of stochastic differential equations. Experience of using MHD output as input for GCR transport