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include physics-informed machine learning, digital twins for turbines and reactors, AI-driven design of energy hardware, predictive maintenance of energy infrastructure, and data-driven modeling of fluid
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. This includes large-scale computational mechanics of energy structures, data-driven mechanics, reduced-order modeling, structural optimization, life-cycle analysis, multiphysics modeling of energy materials, and
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food production Food systems modeling We seek candidates with clear plans for research translation, including collaboration with in-Kingdom and international partners, and a pathway to validate and
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alternative-source production Resource recovery and waste valorization Water system modeling We seek candidates with clear plans for research translation, including collaboration with in-Kingdom and
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can be based on physics-informed neural network, data-driven models, and hybrid simulation models. These developed models can ultimately be deployed for industrial applications of membrane design and
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degradation, and connect them to cell- and pack-level safety performance. · Design model-based and data-driven frameworks for battery management systems, including health monitoring, early fault detection, and
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redistribution of fluids occurs within the wellbore, driven by gravity segregation, which can impact the readings of downhole instruments such as the pressure gauges. In other scenarios, when injecting multiple
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Sensing (DAS) data processing and compression using ML Physics-driven machine learning for geophysical modeling and inversion Thus, the candidate is expected to have or about to have a PhD in a relevant
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part of the Physical Science and Engineering Division. The Composites Lab started at KAUST in 2009 and is an integrated environment for composite science, combining modeling and experimental expertise in
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started at KAUST in 2009 and is an integrated environment for composite science, combining modeling and experimental expertise in a single working environment. OUR MISSION: Support Energy transition by