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Bayesian methods, deep learning, deep generative models, reinforcement learning, graph neural networks. Interviews are expected to happen in July 2025. Applicants are encouraged to guarantee that referees
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Bayesian methods, deep learning, deep generative models, reinforcement learning, graph neural networks. Interviews are expected to happen in July 2025. Applicants are encouraged to guarantee that referees
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modern Bayesian modelling frameworks such as Stan, Turing.jl, and PyMC, including automatic differentiation frameworks, MCMC sampling algorithms, and iterative Bayesian modelling. Special attention will be
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mechanics, such as inferring the instantaneous state of a fluid’s velocity field from sensors embedded in its boundary. The research objective is to find the best way to embed simple partial differential
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-driven algorithms which can solve state estimation problems in fluid mechanics, such as inferring the instantaneous state of a fluid’s velocity field from sensors embedded in its boundary. The research