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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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Login Recently added Development of a GIS-Based Model for Active Citizenry Street-Level Environment Recognition On Moving Resource-Constrained Devices Bayesian Generative AI Explainability and Compact
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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
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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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Bayesian belief networks; Experience in scenario development approaches, e.g. SSPs; Experience in the application of R-based analytical tools for qualitative or semi-quantitative modelling, incl. RQDA
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, natural language processing, transformer based language models, generative image models (e.g., GAN and variational auto encoders), generative models for structured data (e.g., Bayesian networks), Blockchain
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interests in the areas of applied and pure mathematics, and statistics. In Statistics, the School has research strengths in Bayesian and Monte Carlo Methods, Biostatistics and Ecology, Combinatorics, Data
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science which includes fields such as Bayesian statistics, statistical learning, actuarial statistics, computational statistics and statistical methodology. Key Duties and Responsibilities Lead, carry out
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) for engineering systems. Our research covers surrogate modeling, reliability analysis, sensitivity analysis, optimization under uncertainty, and Bayesian calibration. We are known for developing the UQLab software