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Universiteit Amsterdam welcomes applications for a two-year Postdoctoral position in Reinforcement Learning for Stochastic Optimization. The candidate is expected to conduct high-quality research
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understand, explain and advance society and environment we live in. Your role Research in the general domain of stochastic analysis, with special focus on stochastic geometry, such as random fields, random
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role Research in the general domain of stochastic analysis, with special focus on stochastic geometry, such as random fields, random graphs and related structures, limit theorems, stochastic calculus and
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EPFL - Ecole Polytechnique Fédérale de Lausanne, Chair of Stochastic Analysis Position ID: EPFL-POSTDOC [#27659, 1898] Position Title: Position Type: Postdoctoral Position Location: Lausanne
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is looking to hire a research assistant to work with her at the Barcelona School of Economics on a project studying Statistical inference for high-dimensional stochastic differential equations under
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three-year postdoctoral position in stochastic analysis, with a preference for mathematical finance, beginning in September 2026. Qualifications A Ph.D. in mathematics or closely related disciplines is
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coupled particle-and-field stochastic processes following a path integral approach that combines Doi-Peliti and Martin-Siggia-Rose field theories. This method will be applied to model complex stochastic
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applications to the complexity of problems for stochastic games are also expected. The postdoctoral researcher will: * Develop algorithms to solve symbolic computation problems (real and algebraically closed
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energy supply systems, multi-objective and stochastic optimization, advanced statistical analysis, and data visualization. This position offers the opportunity to work with a multidisciplinary team of
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modelling of accreting black holes and/or in observational stochastic X-ray timing and polarimetric analysis.