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Research Associate to contribute to a project focused on robust Bayesian inference with possibility theory. Robust inference is crucial for many real applications in which datasets are invariably corrupted
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at Stockholm University. We have a strong tradition in sampling but areas that we are growing in include, but are not limited to, Bayesian inference, the intersection of statistics and machine learning
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modelling of climate-sensitive infectious diseases, with a particular emphasis on Bayesian hierarchical modeling using Integrated Nested Laplace Approximation (INLA). The work will contribute to ongoing
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Bayesian statistics, statistical computing, spatial statistics, experimental design, and survival analysis. Faculty are active in application areas of neuroscience, geology, biostatistics, psychometrics
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. Please direct all questions about the position to Dr. Jessica Jaynes at jjaynes@fullerton.edu . Statistics at CSU Fullerton The statistics faculty research areas include Bayesian statistics, statistical
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virtual reality systems, code language models, high-level synthesis, Bayesian neural networks, and FPGA-based acceleration. To apply as a Research Associate you must have a PhD (or equivalent) in
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’ or ‘internationally excellent’. The highly research active SP Section comprises 13 permanent academic staff with research interests in Bayesian computational statistics and machine learning, uncertainty quantification
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for a Postdoctoral Research Scientist position in applied mathematics and scientific computing, emphasizing inverse problems in seismology and Bayesian analysis. The position is associated with
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the team’s work across its different content areas. We are seeking a candidate with strong quantitative and statistical modeling skills, particularly in Bayesian methods, who is ready to advance their career
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motif, hence renders the identification of the binding protein difficult. Here we propose for the first time to apply the Bayesian information-theoretic Minimum Message Length (MML) principle to optimise