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the DFG-funded research project ICEBAY, which focuses on Bayesian hierarchical modeling and probabilistic inference for temperature reconstruction by combining borehole thermometry and ice-core data. The
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Your Job: This PhD project develops a Bayesian inference framework for hybrid model- and data-driven modeling of metabolism, with a particular focus on handling model misspecification. By combining
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Machine Learning Seminar Group Advanced Tutorial Lecture Series on Machine Learning Non-Parametric Bayes Tutorial Course (October 9, 16 and 28, 2008) Bayesian statistics in other labs Machine Learning and
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Bayesian optimization and other active learning techniques to guide experimental efforts by identifying optimal chemical compositions and processing conditions of membranes that maximize both selectivity and
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be inferred from models that are incomplete and data that involve errors. For such challenges, Bayesian analysis using Markov Chain Monte Carlo (MCMC) has become the gold standard. For addressing high
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conservation, using participatory modelling approaches (e.g. Causal Loop Diagrams, Bayesian Belief Networks) that bring together diverse knowledge systems. Co-create locally meaningful scenarios of coastal
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analyses is beneficial Expertise in machine learning and Bayesian statistics is beneficial What we offer: Work on a scientifically exciting, socially highly relevant, and globally visible ERC Synergy Grant
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Expertise in machine learning and Bayesian statistics is beneficial Experience in project management is advantageous What we offer: Work on a scientifically exciting, socially highly relevant, and globally
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-informed / simulation-aware modeling Efficient algorithms for design-space exploration (e.g., surrogate modeling, Bayesian optimization, differentiable programming) Hybrid approaches combining data-driven
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of the research project “Unreal engines — Understanding language models through resource-optimal analysis: Implicit Bayesian pragmatic reasoning & emergent causal world models”. The project uses