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models, spatial Bayesian methods, case time series, case crossover. Have experience with the management and analysis of large climate and/or health databases. Have experience with Linux environment and
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observations (DR1), based on this detection method. The candidate will derive cosmological constraints from the modelling of the cluster abundance, using the classical Bayesian framework, and will also
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Science, Telecommunications, Applied Mathematics, or related fields; Solid background in probabilistic modeling, Bayesian inference, information theory, and/or machine learning; Experience with signal processing or decision
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circuit mechanism underlying higher cognitive functions such as multitasking, rule-based reasoning and Bayesian inference). In addition to the above areas, there is extensive expertise available in
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Bayesian machine learning to improve risk management for bridge portfolios. We offer a funded PhD position in an excellent research environment. The project Our infrastructure is aging, and decisions about
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statistical and machine learning techniques, including Bayesian inference and stochastic modelling, the project will quantify and analyse uncertainties in the design and operational performance
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isotopes, TIMS and ICP-MS. B3 Knowledge and experience of project-specific technical models (e.g., Bayesian modelling), equipment or techniques including high-precision CA-ID-TIMS and LA-ICPMS U-Pb
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project team in defining the thesis topic more precisely and will participate in its successful implementation. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5175-AURBES-035
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statistical methods such as dimensionality reduction and Bayesian modeling. This project offers access to a rich, curated clinical dataset and collaboration with leading neurologists, neurosurgeons, and data
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such as: Advanced transportation systems modeling and simulation that could involve integrated machine learning and network equilibrium/simulation, surrogate models/ reduced order emulators or Bayesian