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correlations or more innovative methods of multivariate analysis and we anticipate here an opportunity of using machine learning that could help in predicting properties or classifying sources. A last step will
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technologies, and integrate machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in
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-flexible technologies, and integrate machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 12 days ago
access to GRAME-CNCM (computer music center based in Lyon) facilities, fostering potential collaborations with artists, etc. References [1] Gregorio Giudici, Franco Caspe, Leonardo Gabrielli, Stefano