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models, and associated problems in PDE, with emphasis on identifying both well- and ill-posed examples and the interplay between probabilistic analysis and the analysis of partial differential equations
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with new paradigms for direct solvers of high-dimensional partial differential equations, members of CHaRMNET aim to overcome this challenge. The focus of this position is on structure-preserving
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develop and analyze mathematical models and algorithms that connect partial (and/or stochastic) differential equations, infinite-dimensional optimization, and statistical machine learning. The goal is to
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dynamics using analytical and numerical methods to solve partial differential equations, -- excellent oral and written communication skills. Prior experience in nonlinear waves, fluid dynamics and numerical
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nature, including mathematical biology, mathematical geosciences, applied partial differential equations, environmental and spatial statistics, scientific computing, and the scholarship of teaching and
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differential equations relevant to computational fluid dynamics. These efforts might include Bayesian physics-informed neural networks and neural operators. Bayesian neural networks for approximating piecewise
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for hyperbolic conservation laws and other time-dependent partial differential equations relevant to computational fluid dynamics. These efforts might include Bayesian physics-informed neural networks and neural
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the courses attended on the following topics: Analysis of Partial Differential Equations, Continuum Mechanics and Fluid Dynamics, Functional Analysis, Numerical Analysis, Probability and Stochastic Processes
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trustworthy mathematical models that are calibrated to measurement data. We are motivated by applications in engineering in which the system models are partial differential equations (PDEs) with potentially
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, Germany [map ] Subject Area: Analysis of partial differential equations Appl Deadline: 2025/10/31 11:59PM (posted 2025/09/22) Position Description: Apply *** the listing date or deadline for this position