Postdoc in AI-Driven Grid Flexibility Coordination and Energy Storage Integration

This postdoctoral role focuses on advanced research in AI-driven coordination of grid flexibility and the integration of energy storage systems. The ideal candidate will have expertise in artificial intelligence techniques applied to power systems, particularly in optimizing grid operations and enhancing flexibility through intelligent control strategies. Skills in machine learning, optimization algorithms, and data analytics are essential for developing models that predict and manage energy demand and supply fluctuations. Experience with energy storage technologies, including battery management and system integration, is critical to effectively incorporate storage solutions into grid operations. A strong foundation in electrical engineering, power systems, or a related field is expected, along with the ability to work with large datasets and simulation tools. Familiarity with smart grid technologies, distributed energy resources, and real-time grid management will be advantageous. The candidate should demonstrate proficiency in programming languages such as Python, MATLAB, or similar, and have experience with AI frameworks and tools. Collaboration skills and the ability to contribute to interdisciplinary research projects are important, as this role involves working with experts in energy systems, AI, and control engineering. Overall, this position requires a combination of deep technical knowledge in AI and energy systems, practical experience with grid flexibility mechanisms, and a research-oriented mindset to advance the integration of energy storage within modern power grids.