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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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the same systematics identified in the observables. d) Estimation of cosmological and “nuisance” parameters using Bayesian methods. 4. The research activities provided for the post-doc assignment will
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-changing careers. Learn more about Sandia at: https://www.sandia.gov *These benefits vary by job classification. What Your Job Will Be Like: We are seeking motivated postdoctoral candidates to advance
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received funding from the European Innovation Council and the European Union’s Horizon Europe research and innovation programme under Grant Agreement No.101306664. Where to apply Website https
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partners; - analyze the behavioral traces and verbal data using suitable methods (regression, clustering analysis, Bayesian models); - contribute to the identification of relations between mediation
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simulations, density functional theory (DFT), molecular simulations, or machine-learning potentials. Experience with generative AI, active learning, uncertainty quantification, Bayesian optimization
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Two DTU Tenure Track Assistant Professors in Autonomous Modelling and in Robotic Synthesis of Ene...
) closed-loop materials discovery, e.g., Bayesian Optimization, autonomous analysis of patterns, spectral data or cell-level testing. Experience with predictive control of the synthesis robotics and reaction
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entitled “Beyond Data-Augmentation: Advancing Bayesian Inference for Stochastic Disease Transmission Models”. The overarching aim of the project is to develop the next generation of statistical tools
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, Uncertainty quantification, Approximation Theory, Applied Probability and Bayesian statistics, Optimal Control and Dynamic Programming. Appointment, salary, and benefits. The appointment period is two years
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with cancer. Proven ability to develop novel computational methodologies, including Bayesian generative models, phylogenetic inference tools, and algorithms for multimodal data integration. Demonstrated