PhD Student in Machine Learning and Power Systems

Job summary

Two PhD positions are available focusing on the development of advanced machine learning tools for power systems within a leading research environment. One position will concentrate on physics-informed neural networks integrated with large language models for dynamic simulations, while the other will develop Trustworthy AI Foundation Models for secure grid operations.

Qualifications

• A two-year master's degree (120 ECTS points) or equivalent in engineering, mathematics, computer science, physics, sustainable energy, or related fields.

Responsibilities

• Conduct high-quality research at the intersection of machine learning, data science, and power system simulation.
• Collaborate on international research projects and contribute to teaching and supervision of students.

Skills

• Proficiency in machine learning techniques, statistics, and numerical methods for simulations.
• Knowledge of power system dynamics and optimization.
• Programming experience with tools such as Python, Julia, and Pytorch.
• Familiarity with power system software like Powerfactory, PSCAD, and EMTP.
• Strong English communication skills for presentations and scientific writing.

Education

• Candidates must possess a master's degree or equivalent.

Tools

• Programming languages: Python, Julia, Pytorch.
• Power system software: Powerfactory, PSCAD, EMTP.