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simulate a refined batch of synthetic data. For each batch, the postdoc will estimate Bayes optimal error, an important guide for realistic goals for deep learning. The first batch of synthetic data will be
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reinforcement learning (RL), Bayes adaptive RL, and planning with novel variants of Monte Carlo tree search. You should possess a relevant PhD/DPhil or be near completion together with relevant experience
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computational foundations of that capability and help bridge the gap between Bayes theory and practical application: knowledge integration, developing robust likelihood frameworks, sampler behavior for long
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