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in linear and nonlinear Partial Differential Equations and/or Fluid Mechanics Capability of working within a project team with the goal of achieving outstanding results. Good communication and
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(according to the Instruction of the Ministry of Research, Innovation and Digitalization no. 2260/2023) At least 3 years research experience in Mathematical Analysis/Partial Differential Equations with
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(Partial Differential Equations: Deterministic and Probabilistic Studies), Geometry, and LIMD (Computer Logic and Discrete Mathematics). This diversity of research topics within a single laboratory reflects
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candidate to work in a team on the interdisciplinary StochMan project that integrates elements of stochastic analysis, geometry, partial differential equations, and computational mathematics. An important
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the possibility of extension. We are looking for PhDs in Mathematics, with experience in Hyperbolic Partial Differential Equations (PDEs), or more in general, evolution equation in the sense of Petrowsky, and who
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for Postdoctoral Associate positions in the broad research areas of mathematical analysis and partial differential equations (PDEs). While all applicants with a background in the analysis of PDEs will be considered
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: EDPs2 (Partial Differential Equations: Deterministic and Probabilistic Studies), Geometry, and LIMD (Computer Logic and Discrete Mathematics). This diversity of research topics within a single laboratory
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, United States of America [map ] Subject Area: Analysis - Partial Differential Equations Appl Deadline: 2025/12/01 11:59PM (posted 2025/11/10, updated 2025/10/10) Position Description: Apply Position Description
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The University of North Carolina at Charlotte | Charlotte, North Carolina | United States | 26 days ago
. Preferred Education Skills and Experience: Preferred qualifications include research and teaching experience in mathematics; a strong research interest in partial differential equations, mathematical physics
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, statistical thermodynamics, and numerical methods for partial differential equations. Experience or a strong interest in the study of stochastic fluid models is required. Knowledge of scientific programming