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Field
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environments and inaccurate prior maps, to name a few. In order to cope with these challenges different methods will be developed. Knowledge of Bayesian methods for sensor data fusion, mapping and multiple
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testing, propensity score methods, meta-analysis, Bayesian inference, and a wide range of regression models (linear, logistic, Poisson, negative binomial, lognormal, Cox, mixed-effects, GEE, penalized
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 2 months ago
assessment models using approaches such as Bayesian networks and system dynamics, leveraging domain expertise and statistical tools (e.g., SPSS, Vensim) to model cyber-physical risk scenarios in the maritime
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.) experience with statistical methods (Bayesian statistics, machine learning etc.) We offer Lund University is a public authority which means that employees get particular benefits, generous annual leave and an
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Masters project Supervisors Login Recently added Development of a GIS-Based Model for Active Citizenry Street-Level Environment Recognition On Moving Resource-Constrained Devices Bayesian Generative AI (PhD
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, and visualization are preferred. Prior training in longitudinal data analysis, survival analysis, Bayesian methods, and joint modeling is highly desirable. Experience working with clinical or biomedical
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The Department of Statistics employs about 15 researchers, teachers, doctoral students, and other staff. We conduct research in several areas: analysis of high-dimensional data, Bayesian methods
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collection, pipeline automation, data visualization, and advanced statistical analysis. Candidates must have experience managing large-scale survey datasets, multilevel bayesian modeling, game development, and
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revisiting the study of these latent variable models with a Bayesian point of view and to understand how this evidence lower bound integrate implicit priors on the latent variables. Having a clear
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selection criterion in some extent. This strongly suggests revisiting the study of these latent variable models with a Bayesian point of view and to understand how this evidence lower bound integrate implicit