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decision-making. Key research activities will include multi-parameter optimization of experimental process spaces, investigation of catalyst structure–performance relationships, and development of
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our community. We are now looking for a Doctoral Researcher in AI and Quantum-Inspired Optimization for Sustainable Energy Systems Are you passionate about developing AI-based and quantum-inspired
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techno-economic analysis, life-cycle assessment, mathematical optimization, process-oriented modeling of industrial energy systems, and the analysis of regulatory frameworks. In particular, we focus on
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enabling process monitoring, learning, and policy training while ensuring safety and efficiency. For this, we develop novel learning-based control methods with practical applicability and theoretical
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response; process and energy system modeling; optimization and model predictive control; and applications of artificial intelligence and machine learning to energy systems. The position will involve
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. The interviews will typically take place in January and February of 2026, and our search is expected to be concluded around April 2027. You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/ .
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using building measurements , physics-based simulations and energy-system optimization models. Investigate how tabular foundation models can support energy-system modelling and optimization , including
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optimization of new reactions and for high-throughput synthesis of libraries for biological screening. Additional responsibilities include creating policies and procedures for use of the center’s facilities by
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testing of model-free algorithms for real-time optimization of turbine operating conditions (e.g., yaw set points). Other projects may be assigned by the supervisor depending on skills and technical needs
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extreme environments. You will be involved in research to implement methods for materials design and process development. You will be a creative force in the integration and application of