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career scientist with background in organic geochemistry, statistics, and Bayesian modeling to pursue analyses of paleoclimate biomarker data. The ideal candidate should be proficient with both laboratory
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appreciated. - Advanced statistical modeling (GLMMs, state-space models, stochastic Bayesian programming) in R - Experience with bioinformatics, if possible experience in the use of RAD-seq and/or lcWGS data
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applications. The project aims to address fundamental theoretical questions related to the representation and measurement of the polarization state, as well as the use of Bayesian and/or statistical learning
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, differential equation-based models and/or Bayesian phylogenetics. The annual base salary range for this position is from $77,976 to $95,014, and pay offered will be based on experience and qualifications
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application of conditional diffusion models, flow matching techniques, or related generative approaches, as well as experience working with probabilistic (Bayesian) methods and statistical modelling. Strong
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Bayesian framework and two specific proposed lines of research: (1) constructing suitable priors via neural networks approximations, and (2) enhancing the sensitivity and efficiency of posterior diagnostics
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well as experience working with probabilistic (Bayesian) methods and statistical modelling. Strong writing and programming skills are essential. A proven record of publishing in high-quality journals and presenting
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. Applicants with experience in Bayesian modeling, spatial statistics, mathematical modeling, data integration, uncertainty quantification and/or machine learning are encouraged to apply. The postdoc will also
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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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uncertainties (delays, resources, failures) using various methods, including Bayesian approaches. 3. Optimize the workshop configuration, taking into account scenario variability, by relying on the surrogate