PhD Fellowship: AI-Driven Energy Community Optimization

University of Mons; Belgique; On-site; EUR 26,000 - 28,000; Full time

Benefits offered by this job

International and multidisciplinary环境

Interdisciplinary research

Job summary

University of Mons invites applications for a three-year PhD fellowship within the Horizon Europe project AISCEND, focusing on AI-driven forecasting and energy sharing for community-centered grids. The research combines optimisation, AI, and energy economics, with day-ahead scheduling and energy-management decision support.

The role involves collaboration with European partners, reinforcement learning studies, and validation in living labs in Belgium, contributing to innovative energy systems

Qualifications

• Master’s degree in electrical engineering, energy engineering, computer science engineering or a related engineering field.
• Strong programming (Python, Julia) and quantitative skills; good communication in English.

Responsibilities

• Develop day-ahead scheduling methods integrating renewable generation, flexible demand, storage and electricity-grid constraints.
• Combine mathematical optimisation and artificial intelligence to improve energy sharing and flexibility management in energy communities.
• Investigate reinforcement learning to adapt energy-management decisions to forecast errors and changing operating conditions.
• Collaborate with European partners to integrate methods into an agentic AI platform for coordinated energy management and validate in a Belgian living lab.

Skills

English proficiency

Education

Master’s degree in electrical engineering, energy engineering, computer science engineering or related field

Tools

Python

Julia

Job description

University of Mons invites applications for a three-year PhD fellowship within the Horizon Europe project AISCEND, focusing on AI-driven forecasting and energy sharing for community-centered grids. The research combines optimisation, AI, and energy economics, with day-ahead scheduling and energy-management decision support.

The role involves collaboration with European partners, reinforcement learning studies, and validation in living labs in Belgium, contributing to innovative energy systems