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of statistical analyses, in particular: Exploratory and confirmatory factor analysis, Multilevel analyses (including latent class analysis), Time series analysis, Bayesian inference methods, Regression techniques
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datasets. Apply sensitivity analysis, parameter subset selection, and Bayesian inference to improve model identifiability and predictive capability. Implement computational pipelines in Python, MATLAB, and
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service. We welcome applicants from all areas of statistics. Preference will be given to candidates whose research interests overlap with the existing faculty, particularly causal inference, high
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underlying spatial data, high-dimensional and big data (e.g., data from wearable devices, electronic health records), Bayesian statistics, and learning algorithms as novel data analytical tools in applications
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). -Interest in Bayesian inference. - Knowledge of non-Gaussian models (heavy-tailed, impulsive) is an asset. Additional Information Work Location(s) Number of offers available1Company/InstituteUniversité
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 3 hours ago
are particularly interested in scholars who advance methodological frontiers, such as causal inference, complex systems modeling, implementation science, longitudinal or big-data analytics, community-engaged methods
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. We are interested in candidates with research interests in causal inference or Bayesian methodology, and we also welcome strong applicants from the broader fields of statistics and machine learning
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
of Biostatistics. Specifically, the position works on and provides oversight to several federal and industry research and training grants in the areas of casual inference, Bayesian methods, robust methods, frailty
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
of Biostatistics. Specifically, the position works on and provides oversight to several federal and industry research and training grants in the areas of casual inference, Bayesian methods, robust methods, frailty
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | about 1 month ago
: surrogates, neural operators, active learning, online training, Bayesian methods. Then -- start to work on possible generative methods for active learing (normalizing flows, diffusion models, generative