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Deadline: none (posted 2025/05/13) Position Description: Position Description We are pleased to announce exciting postdoctoral opportunities within Ordinary Differential Equations group at Sun Yat-sen
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, United States of America [map ] Subject Areas: Mathematics / applied mathmetics , Mathematical Sciences , Partial Differential Equations , Statistics Machine Learning Computer Science Appl Deadline: none (posted 2025/08
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of harmonic analysis, partial differential equations, and mathematical physics. The problems to be studied include, but not limited to • Homogenization theory of partial differential equations. • Boundary value
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functional inequalities Rough paths, stochastic differential equations and stochastic PDEs The positions are full-time, fixed-term appointments, with an earliest start date on February 1st 2026. Attractive
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Computational Mathematics invites applications for Postdoctoral Research Associates to join in research efforts of interest to its faculty. Domains of interest include nonlinear partial differential equations
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government agencies (e.g. Defra, Food Standards Agency), industry bodies and F&V producers. You will develop mathematical models, based on systems of nonlinear differential equations combined with asymptotic
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are looking for: a highly motivated researcher with at least 3 years of research experience (possibly as part of the PhD) in a field related to mathematical analysis of partial differential equations (PDEs
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domains. Its strengths span foundational mathematics, algebra, applied mathematics, probability and statistics, financial mathematics, and differential equations, forming a robust, interdisciplinary
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conjecture, -- Langlands program and related problems, -- algebraic geometry and complex geometry, -- partial differential equations and in particular Navier-Stokes equations, -- stochastic analysis
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of Quantum Probability and Operator Algebras, Differential Geometry, Algebraic Geometry, Numerical Methods especially for Stochastic Differential Equations, Harmonic Analysis, and Classical Analysis, each