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, Lausanne 1015, Switzerland [map ] Subject Areas: • stochastic differential equations (SDEs); stochastic partial differential equations (SPDEs); stochastic processes on manifolds; multi-scale stochastic
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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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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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privacy constraints. About the Project The central aim of this project is to pioneer statistical methods for high-dimensional diffusion processes under privacy constraints. While stochastic differential
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year. The expected start date is August 16, 2026, and the end date is May 31, 2028. This opening is in probability theory and stochastic processes with emphasis on stochastic analysis, aligning with
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of self-similar stochastic processes, the so-called Hermite processes. Self-similar processes are stochastic processes that are invariant in distribution under a suitable time scaling. The purpose is
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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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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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the research activities entrusted to the officer take place: This ANR project lies at the interface between statistical learning (mainly deep learning) and combinatorial optimization (mainly stochastic and
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of Bayesian estimation theory, stochastic processes, and statistical inference. Proficiency in scientific programming (Python, MATLAB, C++) and software engineering best practices (Git, testing, documentation