PhD in AI and Renewable Energy Systems: Multimodal Data Integration and Adaptive Monitoring for Digital Twins University of Technology of Belfort-Montbéliard in France

PhD opportunity at the FEMTO-ST Institute (University of Technology of Belfort-Montbéliard, UTBM) in Belfort, France, within the SHARPAC Team of the Energy Department.

The project is titled “Multimodal Data Integration and Adaptive Monitoring for Digital Twins in Renewable Energy Systems” and sits at the intersection of artificial intelligence, computer science, electrical engineering, statistics, and renewable energy systems. The research focuses on multimodal data fusion from heterogeneous energy-system datasets, uncertainty-aware digital twins, adaptive anomaly detection, predictive maintenance, and inverse reinforcement learning for operational decision support. The broader goal is to improve resilience and reliability in hybrid renewable energy systems (HRES).

The host laboratory is a CNRS-affiliated research institute, and the work is described as highly interdisciplinary, combining AI methods with power-system and energy-system optimization. The doctoral specialty is Electrical Engineering (Section 63).

Eligibility: applicants should hold, or be in the final year of, a Master’s degree in Electrical Engineering, Computer Science, Applied Mathematics, or a related field. Strong skills in AI, machine learning, data analytics, optimization, and power/energy systems are valued. Experience in machine learning, signal processing, or scientific programming is an advantage. A good level of English is required, and an English language certificate is strongly recommended for non-native speakers.

Funding: MESRI-funded position with a gross monthly salary of about €2300. The PhD duration is 36 months.

Application deadline: 11 May 2026. Interviews are scheduled for 25 May 2026, and the contract start date is 1 October 2026.

How to apply: send the application directly to the supervisors, including a cover letter, at least one reference letter, diplomas or completion certificates, transcripts, ranking certificates if available, passport copy, and a detailed CV.