Enhancing Renewable Energy Integration Through Advanced AI-Based Forecasting Models

We invite applications for a PhD position focused on developing next-generation AI-based forecasting models to enhance renewable energy (RES) integration into power systems. This research emphasizes improving prediction accuracy for renewable energy production (particularly solar and wind) through advanced machine learning techniques that capture spatial-temporal dependencies, quantify uncertainty, and enable real-time decision-making. The project will explore hybrid AI architectures, weather-integrated forecasting systems, and edge-deployable intelligent models. The goal is to improve renewable energy planning, grid stability, and operational efficiency through reliable and interpretable forecasting tools. Applicants should have a masters degree in electrical engineering, computer science, or a related field, strong analytical and programming skills, and an interest in AI-driven ...