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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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, kernel machines, decision trees and forests, neural networks, boosting and model aggregation, Bayesian inference and model selection, and variational inference. Practical and theoretical understanding
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polycrystalline material during plastic deformation in order to eventually predict the manner in which materials deform and fail. As a first step, we wish to infer a distribution of the directions of deformation
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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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the weblike distribution of galaxies in large galaxy redshift surveys, with the corresponding velocity flows inferred from measured galaxy peculiar velocities. These measurements are to be converted into a
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work in close partnership with the wet-lab team and use novel computational approaches and algorithms including A.I. and Bayesian statistical methods to infer causal relationships between mtDNA variants
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the corresponding velocity flows inferred from measured galaxy peculiar velocities. These measurements are to be converted into a multiscale analysis of the mass distribution, as well as that of the flow field
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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