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applications for a three-year PhD Stipend from October 1st or soon hereafter in dynamic modelling, simulation and optimization of Power-to-X processes for renewable fuel production. The project is primarily
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Aalborg University, Department of Energy, Campus Esbjerg, invites applications for a three-year PhD Stipend from October 1st or soon hereafter in dynamic modelling, simulation and optimization
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Technology, and the PhD student will be positioned in the Esbjerg Energy section. The position is part of the internally funded research project SURGE: Speed-optimized USVs for Robust Guidance and Offshore
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, flexibility, and operational efficiency of existing battery recycling processes. Specifically, it aims to improve and optimize cost and recovery efficiency of existing scaled recycling technologies and develop
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while maintaining computational efficiency through lower-fidelity simulation of non-critical regions, (ii) virtual sensing techniques for load and stress estimation from limited and optimally placed
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, deterministic systems. You model them, you optimize them, you operate them. That paradigm is breaking down. As electricity replaces fossil fuels, industrial systems must operate under fundamentally new conditions
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perception, optimization, or control will be an advantage. The candidate should be comfortable with scientific programming, for example in Python and common machine-learning frameworks such as PyTorch
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while maintaining computational efficiency through lower-fidelity simulation of non-critical regions, (ii) virtual sensing techniques for load and stress estimation from limited and optimally placed
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NAS that considers accuracy, latency, energy, and carbon at the same time. Delivering a carbon-aware NAS framework that generates Pareto-optimal model architectures and model libraries whose variants
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the system to learn optimal adjustment policies directly from interaction with the physical infrastructure. Anomaly detection and fault diagnosis. The candidate will develop a multi-level diagnostic framework