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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
covers the object's entire life cycle and uses real-time data sent by sensors on the object to simulate its behavior, monitor operations, and anticipate its functioning. Partial differential equation (PDE
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of an object or medium from measurements of waves that have propagated through it. Mathematically, such problems lead to large-scale nonlinear inverse problems governed by partial differential equations (PDEs
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differential equations (PDEs). Full-waveform inversion is a powerful approach to such problems, but its practical use is limited by the strong nonlinearity of the inverse problem and by the computational cost
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new approach has emerged that integrates data and mathematical models through neural networks. This has led to the development of a method for solving partial differential equations (PDEs) known as
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, energy principles, and gradient-flow techniques can be used to analyse the existence, regularity, stability, and long-time behaviour of solutions to kinetic PDEs. The project aims to develop rigorous
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Microlocal analysis explores the classical/quantum correspondence in partial differential equations (PDEs). For example, the concept of symbol quantisation in the theory of pseudodifferential
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applied to regression, classification, and the solution of time-dependent partial differential equations (PDEs), such as large-scale tsunami simulations. The project involves two doctoral researchers with
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on the intersection of learning theory, PDEs, and systems & control, likely using RKHSs (or similar function spaces), Koopman operators, and neural networks to study interesting classes of controlled PDEs, develop
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Inria, the French national research institute for the digital sciences | Sophia Antipolis, Provence Alpes Cote d Azur | France | 3 months ago
Website https://jobs.inria.fr/public/classic/en/offres/2026-10248 Requirements Skills/Qualifications Expertise in computer graphics and AI, possibly including physical simulation and PDEs. Knowledge of C/C
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of analysis of partial differential equations (PDEs). The PhD candidate will be supervised by Havva Yoldaş and co-supervised by Raphael Winter (Cardiff University). The research topics primarily revolves around