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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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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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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
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optimization of quantum algorithms for hybrid quantum simulators. Applicants should have a PhD in Physics, Chemistry, Computer Science, or a closely related field. To apply, a CV, a brief statement of
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optimization of quantum algorithms for hybrid quantum simulators. Applicants should have a PhD in Physics, Chemistry, Computer Science, or a closely related field. To apply, a CV, a brief statement of