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University of Mons
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PhD Fellowship in AI-Driven Optimisation for Energy Communities University of Mons in Belgium
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Nov 30, 2026
Country
Belgium
University
University of Mons
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About this position
The Faculty of Engineering at the University of Mons is offering a three-year PhD fellowship within the Horizon Europe project AISCEND on AI-driven, socially embedded forecasting and energy sharing for community-centered grids.
The doctoral project sits in the Electrical Power Engineering Unit and the Power Systems and Markets Research Group, bringing together power systems, optimisation, artificial intelligence, and energy market thinking. The successful candidate will work on methods for day-ahead scheduling in energy communities, combining renewable generation, flexible demand, storage, and grid constraints. A major part of the work is to develop optimisation and learning approaches that improve both decision quality and computational efficiency.
The research agenda includes decision-focused learning, machine-learning-assisted optimisation, and reinforcement learning for adapting energy-management decisions to forecast errors and changing operating conditions. The project also contributes to an agentic AI platform for coordinated energy management in collaboration with European partners.
The methods developed in the PhD will be tested and validated in a Belgian living lab involving energy communities supported by IDETA and in collaboration with the distribution system operator ORES. The practical context emphasises collective self-consumption, user comfort, voluntary participation, and human-in-the-loop decision-making, giving the project a strong applied and societal dimension.
The position is based in Mons, Belgium, within an international and multidisciplinary research environment connected to a European consortium. The fellowship is framed by the Horizon Europe project and offers exposure to collaborative research, scientific publication, conferences, workshops, and mobility activities across Europe.
Funding details
Available
What's required
Applicants should hold a Master’s degree in electrical engineering, energy engineering, computer science engineering or a related engineering field. Strong programming skills in Python and Julia and strong quantitative skills are required. An interest in electric power systems, optimization, machine learning and energy economics is essential, together with good communication skills in English. Excellent applicants able to start immediately will be given precedence. Languages: English at excellent level. Research experience of 1 to 4 years is indicated.
How to apply
Send an updated CV, a list of scientific publications, and contact details for two professional or academic referees by email to [email protected] and [email protected]. Best candidates will be invited for an online interview.
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Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.