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development. Experience with implementing statistical learning or machine learning (e.g. Bayesian inference, deep-learning). Programming skills in Python and experience with frameworks like PyTorch, Keras, Pyro
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human behavior. Preference will be given to candidates with 1) strong knowledge of Bayesian statistical and computational techniques; (2) prior track record of implementing and applying Bayesian
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at the intersection of systems neuroscience and computational modeling. Our lab is broadly interested in Bayesian inference, perception, multisensory integration, spatial navigation, sensorimotor loops, embodied
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and PhD students. Research spans a wide range. Current interests include: Bayesian statistics; modelling of structure, geometry, and shape; statistical machine learning; computational statistics; high