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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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of the following areas: Image processing, partialdifferential equations, scientific computing, deep learning.•Solid programing skills. Knowledge of Python, Tensorflow/Pytorch, and Mathematica.•Fluent
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affiliated with the Optimization and Optimal Group at RICAM, located in Linz/Austria. The hired person will work on optimization and optimal control related to partial differential equations with emphasis
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educational programs. The postdoctoral fellowship is funded by the Carl Trygger Foundation and focuses on analysis or numerical analysis of partial differential equations. Subject area for the position
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Okinawa Institute of Science and Technology, Analysis and Partial Differential Equations Unit Position ID: 3260 -POSTDOC [#26877] Position Title: Position Type: Postdoctoral Position Location: Onna
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differential equations. - Lipschitz geometry. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR7586-ANDBEL-001/Default.aspx Work Location(s) Number of offers available1Company
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, United States of America [map ] Subject Areas: Computer Science Mathematics / applied mathmetics , Mathematical Sciences , Partial Differential Equations , Statistics Machine Learning 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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of the probability and analysis groups. Projects may include, but are not limited to: Analysis on metric spaces including fractals Heat kernel estimates and functional inequalities Rough paths, stochastic differential
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Ph.D. in Geosciences or a related field. Preferred Qualifications: Prior experience in river modeling, river-lake network analysis and biogeochemistry. Demonstrated ability to solve complex differential