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Postdoc in Stochastic PDEs for Transport Networks Reference number REF 2026-0323 Do you want to contribute to shaping the future of public transport through mathematics? Join an interdisciplinary
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 9 hours ago
Stochastic Optimal Control”. Background or expertise in one or more of the following areas will be considered when selecting candidates: Machine Learning, Neural Networks, Numerical solutions of
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variability. For this, you can include stochastic forward passes or measure latent variability. Finally, you should enable robust out-of-distribution detection vial well-calibrated uncertainty estimates
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<span lang="en">Leipzig University</span> | Leipzig, Sachsen | Germany | about 6 hours ago
of freedom of an active system can we actually control, and at what energetic cost? You will help to build a quantitative framework for controlling active matter with light, bridging stochastic
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coupled to chemical reactions, stochastic dynamics and noise-induced transitions, and the interplay between spatial structure and temporal dynamics. Analytical calculations are combined with numerical
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, but are not limited to, stochastic partial differential equations, optimal transport, gradient flows, uncertainty quantification, model order reduction, data assimilation, optimal control, and their
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numerical methods in partial differential equations, in connection with uncertainty or data science. Specific fields of interest include, but are not limited to, stochastic partial differential equations
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. Nowak. “Evolution of Cooperation in Stochastic Games.” Nature 559, no. 7713 (July 2018): 246–49. https://doi.org/10.1038/s41586-018-0277-x. [3] McNamara, John M. “Towards a Richer Evolutionary Game
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together to integrate both into a single algorithm: Developing theory for trajectory-centric stochastic optimization under non-ergodic dynamics; Implementing practical RL algorithms that optimize long
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algorithm: Developing theory for trajectory-centric stochastic optimization under non-ergodic dynamics; Implementing practical RL algorithms that optimize long-term performance of individual agents