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guidance, navigation, and control (GNC) systems. The successful candidate will develop and validate Bayesian and non-Gaussian estimation algorithms, data assimilation methods, and tracking frameworks
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Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case of dynamic sequential inference and probabilistic
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experience in one or more of: large-scale data analysis, time-series photometry, spectroscopy, astrometry, Bayesian/statistical inference, and/or software development for astronomical datasets. Department
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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