Détail du poste
Établissement : Mines Paris-PSL École doctorale : SFA - Sciences Fondamentales et Appliquées Laboratoire de recherche : Centre de Mise en Forme des Matériaux Direction de la thèse : Elie HACHEM ORCID 0000000222026397 Début de la thèse : 2026-10-01 Date limite de candidature : 2026-08-15T23:59:59 .. The glass industry, a key sector in European strategic materials production, is currently undergoing a profound transformation driven by the urgent need to reduce its carbon footprint while maintaining high standards of productivity and product quality. One of the most promising pathways toward decarbonization is the electrification of glass furnaces. While electrification significantly reduces greenhouse gas emissions, it also introduces new challenges in furnace operation, thermal management, equipment lifetime, and process stability.
In this context, advanced computational modeling and artificial intelligence offer powerful opportunities to better understand, predict, and control these complex industrial systems. By combining physical models with operational data, digital twins can provide real-time insight into furnace behavior and support improved operational decisions.
This PhD is part of the ANR Industrial Chair TwinHeat, which brings together five major partners: three leading glass manufacturers, a furnace designer, a software developer, and the Centre de Mise en Forme des Matériaux (CEMEF) at Mines Paris - PSL. The ambition of the program is to develop a new generation of AI-enhanced digital twins capable of reproducing and assisting the operation of industrial glass furnaces under evolving energy and process conditions.
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Publiée le 26/05/2026 - Réf : 3029d88d6ad4fd724dce59e5f8eb7083
