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parameters to identify regimes that ensure both flame stability and low pollutant emissions. Machine learning techniques have recently shown promise for Design of Experiments (DoE) and interpretation of large
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experimental data (from ex-situ and in-situ measurement). Therefore, she/he will develop a way to optimize/guide the experiments trough artificial intelligence approach (machine/deep learning) that he will
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 19 days ago
-tutelle agreement, further strengthening the international dimension of their training and research. Assignment. Effectively protecting personal data is challenging. A large number of protection mechanisms
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well as decentralized machine learning algorithms for large-scale clouds with dynamique parameters. -- Conception of machine learning algorithmes for resource allocation -- Numerical experiments -- Drafting research
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: electronic structure calculations (plane wave DFT if possible), statistical thermodynamics, molecular dynamics. Skills in Python, bash scripting, Fortran 90 and machine-learning would be appreciated. The PIIM
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Arts et Métiers Institute of Technology (ENSAM) | Paris 15, le de France | France | about 1 month ago
. This issue can have safety implications, particularly in closed-loop setups. Physically Informed Machine Learning (PIML), and in particular Physics-Informed Neural Networks (PINN), are less dependent on data
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4 Sep 2025 Job Information Organisation/Company Université Paris-Saclay (UPS) Research Field Engineering » Industrial engineering Researcher Profile First Stage Researcher (R1) Positions PhD
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4 Sep 2025 Job Information Organisation/Company University of Paris-Saclay Research Field Engineering » Industrial engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 1 month ago
arithmetic cores for FPGAs). The team hosts 6 faculty, 6 PhD students, 3 postdocs, 2 engineer, and multiple research interns. Additional information can be found on team website: https://team.inria.fr/emeraude