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We are looking for a researcher to develop and implement tools for analysis of output from Bayesian inference under phylogenetic models. About the position A researcher position is available in
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(e.g., maximum parsimony; Bayesian inference), and utilizing these phylogenies to quantify evolutionary rates, directionality of trends, and patterns of morphological space occupation. You will have (or
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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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computing skills ● Strong experience with any of the following: ○ Bayesian statistics ○ Machine learning methods ○ Causal inference ○ Vaccine epidemiology research ○ Infectious disease modeling ● Strong
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possible thereafter. The aim of this project is to advance the development of multi-trait Bayesian linear regression models that enable the sharing of genomic information across traits and biological layers
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position We welcome applicants with a strong background in machine learning, causal inference, and statistics, who are eager to contribute to cutting-edge research at the intersection of these fields
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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
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of Physics and Technology, Mathematics and Statistics, and Computer Science. More about the position We welcome applicants with a strong background in machine learning, causal inference, and statistics, who
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); mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; and statistical machine learning. More about the position The position is