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hierarchical, contextual knowledge for complex multi-modal scene understanding Neuro-symbolic architectures for representation, learning, reasoning and inference Biologically-inspired metacognitive AI paradigms
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approaches. Experience in programming in R, using GitHub, and doing Bayesian statistical analyses with the use of MCMC samplers such as JAGS, STAN, or NIMBLE. Point of Contact Justina Eligibility Requirements
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skills: Demonstrated experience in modeling and applied statistics including machine learning, Bayesian statistics, multivariate statistics, model assisted estimation, rarefaction, or wildland fire
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