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well as knowledge to support activities related to optimization methods across integrated energy systems and energy markets. The position is offered in relation to the research group iGRIDS- Intelligent Energy
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expected evolution of these critical properties as the basis for safe reinforcement learning (RL) for on-line optimal control”. In particular, the stipend will investigate enhancement of RL controllers in
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physical modelling in such facilities, but also one that can contribute to the development of the numerical modelling in the group. Your work tasks The candidate will contribute to the teaching and research
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the development of innovative and energy-efficient thermochemical processes that enable a sustainable, de-fossilized carbon economy. We explore renewable carbon sources and investigate optimal conversion pathways
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specialization, medicine, and related fields. CNAP maintains an extensive international network and participates in numerous global research initiatives, providing an inspiring and collaborative environment
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projects in corporation with industry partners. Teaching will primarily be in control theory, hydraulics, dynamic systems, and optimization, but also in other study groups at the University. Furthermore
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materials, and will develop AI-driven Bayesian decision modelling for the optimization of experiments. Further, the candidate will support the development of safety formats and calibration of safety factors
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modeling, optimization techniques, hybrid testing and digital twins. Furthermore, the position aims at incorporating machine learning to drive innovation in the areas. Possible applications are within