PhD in AI-Driven Digital Twins for Energy-Efficient Glass Furnaces Mines Paris - PSL in France

PhD opportunity at CEMEF, Mines Paris - PSL - CNRS within the ANR Industrial Chair TwinHeat project.

The project is titled AI-Driven Digital Twins for Energy-Efficient Glass Furnaces and focuses on the intersection of artificial intelligence, reinforcement learning, simulation-based learning, industrial data analytics, heat transfer, and thermo-fluid dynamics. The research aims to develop AI-powered digital twins for industrial glass furnaces to support monitoring, prediction, optimization, and process control under real operating conditions.

The PhD will be hosted at CEMEF in Sophia-Antipolis, France, in close collaboration with industrial partners including major glass manufacturers, furnace designers, and software developers. The work combines physics-based modeling with machine learning and access to real industrial data, high-performance computing, and advanced simulation tools.

Research themes include reinforcement learning for process control and optimization and data-driven modeling from industrial production data. The candidate will work on intelligent methods for furnace operation, anomaly detection, pattern extraction, and expert-system support for decision-making.

Eligibility highlights: Master’s degree completed or in progress in fluid mechanics, thermal engineering, applied mathematics, computational science, or AI. Strong skills in heat transfer, fluid mechanics, numerical methods, Python and/or C++, and English communication are preferred. Experience with machine learning, reinforcement learning, HPC, or industrial data analysis is an asset.

Funding details: 3-year PhD starting Fall 2026, with a listed gross annual salary of approximately €27,000 before tax.

Contacts listed in the post: Elie Hachem and Franck Pigeonneau at Mines Paris - PSL / CEMEF.