PhD Candidate in AI and Electricity Markets

Job summary

This PhD position focuses on the intersection of AI algorithms, optimal control, and game theory, specifically addressing the role of AI agents in electricity markets. The candidate will develop competencies in multi-agent systems, learning, and optimization while tackling significant challenges in market dynamics and design.

Qualifications

• A two-year master's degree (120 ECTS points) or equivalent academic level.
• Background in Systems and Control, Optimization, Game Theory, Multi-agent Systems, Reinforcement Learning, Algorithms, or Applied Mathematics.
• Basic programming skills (e.g., Python, Julia).
• Proficient in English.

Responsibilities

• Model AI-driven learning dynamics in electricity markets.
• Analyze market equilibria focusing on safety and learnability.
• Develop algorithms to identify and characterize adverse market outcomes.
• Design, test, and optimize market rules to guide multi-agent learning dynamics.
• Combine theoretical analysis with numerical experiments.
• Communicate findings through publications and presentations.

Skills

• Strong analytical and computational skills.
• Experience in theoretical and applied research in relevant fields.

Education

• A master's degree in a relevant field is required.

Tools

• Familiarity with programming languages such as Python or Julia is necessary.