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Field
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well as uncertainty-aware decision-making. The aim of these new algorithms is to develop policies that are robust, interpretable, and relevant for epidemic preparedness and response. As postdoctoral researcher you
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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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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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of analytics into production systems Knowledge of experimental design, uncertainty quantification, scientific machine learning, or digital twin methodologies Experience collaborating across national laboratories
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, stochastic, robust, and multi-objective optimization. Conduct analyses of industrial system resilience, competitiveness, and operational performance under uncertainty. Support model development for co
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a postdoctoral researcher, you will: Integrate hybrid traffic models and data assimilation methods into a coherent prediction framework. Develop uncertainty quantification methods and explainable and
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science. It offers a novel perspective on understanding and managing uncertainty in large-scale infrastructure systems. For more details, see https://research.chalmers.se/en/project/12873 Who we are looking
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intelligence to analysis of experimental data. Of particular interest will be new approaches for tackling multimodal data, quantifying uncertainty, providing rigorous theoretical guarantees, and modelling
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(e.g. model-aided, convergence analyses, universal), data-driven detection and estimation, robust adaptive filtering / beamforming for radar/sonar under modeling uncertainties. In addition to research
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. Develop uncertainty quantification methods and explainable and trustworthy AI approaches. Design visualisation to support decision-making by traffic operators and strategic advisors. Collaborate closely