Contribute to research activities on ML-based methods for power system monitoring
Investigate, deploy and refine foundation models for representing power grid topology, measurements, and operating conditions
Combine ML-driven methods with numerical optimization and power system physics
Evaluate the proposed methods through simulation studies and benchmarking
Report and disseminate results within the team, write technical documentation, and contribute creative ideas towards industrial implementation.
Requisiti principali
Enrolled in an MSc program in Electrical Engineering, Computer Science, Applied Mathematics, or a related field
Strong background in numerical optimization. Power system knowledge is a plus
Good knowledge of machine learning and deep learning. Exposure to graph neural networks, foundation model or machine learning adaptation strategies is a plus
Experience in Python or C++ programming and MATLAB
Experience with PyTorch or similar deep learning frameworks
Excellent communication skills, team player attitude, initiative, and creativity
