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, optimization, partial differential equations and topological data analysis. Currently, there are about 25 graduate students within the subject Mathematics and about 30 graduate students within the subject
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
, non-linear partial differential equations, harmonic analysis, geometric analysis, mathematical data science, computational mathematics, mathematical physics, probability/stochastics, and applied
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
applications for a Postdoctoral Research Associate positions in the field of Analysis, broadly interpreted and including harmonic analysis, the analysis of partial differential equations, dynamical systems
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will work with nonlinear partial differential equations, constitutive modelling, and numerical methods to simulate large-scale mass-movement events, with the aim of improving our understanding of flow
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algebraic equations, partial and ordinary differential equations, integro-differential equations, difference equations optimization with constraints, calculus of variation, scaling methods, approximation
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, representation theory, number theory, algebraic and geometric topology, non-linear partial differential equations, harmonic analysis, geometric analysis, mathematical data science, computational mathematics
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of partial differential equations (PDE). Examples of models in the scope of the project include particle models, stochastic PDE and models from fluid dynamics and machine learning. What skills are important in
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, scientific computation, probability, optimal control, ordinary, partial, and stochastic differential equations, and dynamical systems; and applications of mathematics to biology, finance, and industrial
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map Computational modeling of bone regeneration (partial differential equations) Bringing novel, cutting-edge approaches (e.g. PINNs) to modeling of regenerative processes Parameter optimization and
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framework of Bonneton (2023). This approach allows to « discover » variables in pre-defined partial differential equations on series of data (time-domain technique). Recent tests conducted with both lidars