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MINES Paris - PSL

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PhD in Trustworthy AI for Predictive Control of Multi-Energy Systems Mines Paris-PSL in France

Degree Level

PhD

Field of study

Computer Science

Funding

Funded PhD position under other public funding, supported by the PEPR FutuRE project funded under France 2030. The thesis is linked to the European project Fair4Communities (2027-2030).

Deadline

Oct 23, 2026

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Country

France

University

MINES Paris - PSL

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Keywords

Computer Science
Electrical Engineering
Mathematics
Reinforcement Learning
Power System
Applied Mathematic
Renewable Energy Systems
ML

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About this position

PhD opportunity at Mines Paris-PSL, Centre PERSEE, in Sophia Antipolis, France, on Trustworthy AI for Predictive Control of Multi-Energy Systems.

The thesis focuses on low-carbon multi-energy systems that integrate electricity, heat, gas, hydrogen, storage, renewable generation, and flexible demand. The research combines energy systems, predictive control, reinforcement learning, physics-informed AI, and real-time simulation to develop safe and reliable AI controllers for complex infrastructures.

Key topics include digital twins, uncertainty-aware control, robustness, explainability, safe operating boundaries, distributed control, and Hardware-in-the-Loop validation. The project aims to ensure real-time feasibility and physical consistency while exploiting flexibility across multi-energy networks.

The position is supported by the PEPR FutuRE program funded under France 2030, with links to the European project Fair4Communities (2027-2030).

Eligibility: Engineer and/or Master of Science degree. Applicants may apply before receiving the master's degree, but the PhD will start only after the degree is obtained. A strong background in at least two of the following is expected: systems control, artificial intelligence/data science/machine learning, applied mathematics/statistics/probabilities, and power systems. Programming skills are required; good French is desirable and excellent English is required.

How to apply: Send a CV, motivation letter, transcripts, last diploma, and contact details of two referees by email. Use the subject line PHD-2026-ERSEI-FUTURE-PredControl. Contact Prof. Georges Kariniotakis, with copy to Dr. Sergio-Daniel Montana-Salas.

Deadline: 2026-10-23. The position remains open until a suitable candidate is found.

Funding details

Funded PhD position under other public funding, supported by the PEPR FutuRE project funded under France 2030. The thesis is linked to the European project Fair4Communities (2027-2030).

What's required

Engineer and/or Master of Science degree; candidates may apply before obtaining the master's degree, but the PhD will start only after the degree is successfully obtained. Strong general and scientific culture, good analytical, synthesis, innovation and communication skills, adaptability, creativity, motivation for research, coherent professional project, and programming skills are expected. The successful candidate should have a solid background in two or more of the following: systems control, artificial intelligence/data science/machine learning, applied mathematics/statistics/probabilities, and power systems. Good French is desirable and excellent English is required.

How to apply

Send a CV, cover letter, copies of transcripts and last diploma (in English or French), and contact details of two referees by email. Use the email subject acronym "PHD-2026-ERSEI-FUTURE-PredControl". Contact Prof. Georges Kariniotakis, with copy to Dr. Sergio-Daniel Montana-Salas.

More information can be found here

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