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, as part of the development, one position located in Görlitz as Research Associate / PhD student (f/m/x) Integration of CMOS detector technology into the Universal Bayesian Imaging Kit (UBIK) (subject
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and Bayesian methods) and population studies (nonlinear mixed-effects modeling methods) and hypothesis testing Comprehensive knowledge of the concepts underlying physiological modeling and systems
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tenured/tenure-track faculty and nine full-time instructors. Current research areas of the faculty include survival and reliability analysis, Bayesian statistics, latent variable methods, item response
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exploration strategies that go beyond traditional techniques such as linear programming or deterministic solvers. You will work on cutting-edge methods including: Bayesian optimization Surrogate modeling
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received by November 1, 2025. Preferred skills: Demonstrated experience in modeling and applied statistics including machine learning, Bayesian statistics, multivariate statistics, model assisted estimation
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-based, Bayesian or matrix factorization methods for multi-omics integration. Ability to independently perform data analysis and scientific interpretation based on omics data at an internationally
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and carbon cycle model-data integration using the CARDAMOM Carbon-Water Bayesian model-data integration framework. The candidate will help advance global land biosphere estimates of biomass, water
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learning models, including their strengths, deficiencies, and strategies for (hyper)parameter optimization. Prior use of Bayesian optimization or other relevant active learning algorithms is preferred
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open-ended position. Applicants are invited from any area of applied statistics, including statistical or actuarial data science. Those working in actuarial science, Bayesian statistics, statistical
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The relationship between the information-theoretic Bayesian minimum message length (MML) principle and the notion of Solomonoff-Kolmogorov complexity from algorithmic information theory (Wallace and