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Max Planck Institute of Animal Behavior, Radolfzell / Konstanz | Konstanz, Baden W rttemberg | Germany | 11 days ago
analytical skills (Frequentist and Bayesian statistical frameworks) Experience in collecting and/or analyzing observational data on animal behavior, including ‘focal and party follow’ studies, as well as ‘ad
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incorporate methods that integrate: - Mendelian randomization and genetic instruments - Bayesian hierarchical models and Gaussian graphical models - Multi-layer data integration across tissues and omics
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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 dimensional parameter
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mathematical background Core skills: Probability and statistics. Estimation, Bayesian inference, uncertainty quantification and calibration (proper scoring rules, reliability diagrams, ECE), experiment design
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, reachability approaches or Bayesian filtering and develop a robust prediction algorithm. These dynamic predictions must then be integrated into a map representation to be included and used in the path planning
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workflows across different scales (e.g. multi-fidelity Bayesian optimization). Teaching responsibilities include courses in the university’s bachelor and master programs such as Industrial Biotechnology and
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Experiments (DoE) and Bayesian optimization, manage research data using the NOMAD research data infrastructure, and apply data-driven optimization strategies. Analyze and interpret experimental data
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Brandenburgische Technische Universität Cottbus | Cottbus, Brandenburg | Germany | about 2 months ago
candidate is expected to incorporate innovative approaches into their research that connect classical probabilistic models with modern deep learning architectures. Examples include Bayesian deep learning
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European Molecular Biology Laboratory (EMBL) | Brandenburg an der Havel, Brandenburg | Germany | about 2 months ago
modelling, foundation models, cross-domain/-modality learning, explainable AI and mechanistic interpretability, representation learning, Bayesian inference, causal inference, active learning, AI-based agents
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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