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ecosystems where interconnected multi-agents interact strategically in dynamic and uncertain environments. While Artificial Intelligence (AI) optimizes predictions or policies, energy systems are inherently
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optimization strategies, including reinforcement learning (RL) and optimal control approaches for state preparation and measurement protocol design under hardware constraints. Develop open-source software and
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for multimode bosonic and hybrid quantum systems (including open-system and non-Hermitian effects). Design noise-resilient control and optimization strategies, including reinforcement learning (RL) and optimal
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dynamic and uncertain environments. While Artificial Intelligence (AI) optimizes predictions or policies, energy systems are inherently multi-agent, strategic, and resource-constrained. Each agent has its
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requirements at the energy edge. Further, you will incorporate compliance-by-design AI architectures and models and validate our solutions across key energy use cases such as energy market optimization (demand
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Experience with machine learning theory, evaluation metrics, algorithmic fairness, statistics, or optimization is an advantage Language requirement: Good oral and written communication skills in English
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. Advanced machine learning, reinforcement learning, and agent-based optimization techniques will be developed to reduce voltage deviations, cut active power curtailment, and improve system adaptability under
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these systems in both classical and quantum regimes, we aim to develop new methods for solving complex optimization problems and advancing machine learning architectures. The research involves investigating how
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15th August 2026 Languages English Norsk Bokmål English English Are you interested in work motivation and optimal functioning at work? PhD Research Fellow in Management: Motivation Apply
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. Competence in the theory of the finite element method is an advantage. Competence in the theory of numerical optimization is an advantage. Experience from high-performance computing is an advantage. Applicants