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multidisciplinary research in energy markets, optimization, game theory, and machine learning. Our team of 13 members (link ), from 10 different nationalities, values diversity and includes experts from a range of
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, preferably Reinforcement Learning (e.g., Q-learning, Deep Q-Networks) or other control algorithms. Proficiency in Python, MATLAB, or similar for data analysis, modeling, or AI implementation. Strong written
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learning techniques, as well as methodological issues related to AI (e.g. the fairness and transparency of algorithms) Energy, Environment and Resources Firm Behavior, Innovation and the Functioning
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