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Field
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within trusted digital environments. Their research focuses on ontology-driven conceptual modelling, FAIR data stewardship, and model-driven system/service engineering, dealing with data-driven services
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Three PhD positions at TU/e in collaboration with Canon Production Printing, combining polymer science, rheology, and computational modeling to create the inks and coatings of tomorrow. Information
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loads in power system dynamics and stability as system strength continues to decline. Building on existing frameworks such as the WECC Composite Load Model (CLM), you will develop and validate data-driven
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stability as system strength continues to decline. Building on existing frameworks such as the WECC Composite Load Model (CLM), you will develop and validate data-driven methods for load identification and
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PhD project: Modelling Reliability and Resilience of Hydrogen Systems for Improved Safety and Sustainability Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering
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-informed machine learning (PIML) with domain-specific engineering knowledge. By embedding physical laws and corrosion mechanisms into data-driven models, the research will produce more accurate
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as early indicators of anthropogenic and climate-driven change. However, limited understanding of the processes shaping species’ biogeographic distributions constrains our ability to predict ecological
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) Data-driven surfactant identification and ii) Novel surfactant development. This PhD position is part of a multidisciplinary European consortium with high relevance to the biobased and biotech sectors
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performance. The research focuses on suitable domain models and the required model transformation, analysis, and synthesis approaches. We require candidates for PhD 2 to have good software engineering and
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of Electrical Engineering. Project description: Autonomous vehicles for mining and mobile robotics for industrial processes require complex motion planning as well as safe model-based predictive control and