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universities. The transition towards electrified and energy-efficient energy systems poses significant challenges in predicting the coupled behaviour of thermofluid, electromagnetic, and rotordynamic processes
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mechanistic and reliable service-life prediction models for concrete infrastructure, supporting improved durability design, maintenance planning and resilience of reinforced concrete structures exposed
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to develop an AI-enhanced Digital Twin framework for predictive maintenance and energy optimization in industrial environments. The research will investigate the integration of Industrial Internet of Things
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reliably assess fatigue damage and predict remaining lifetime, enabling proactive maintenance strategies that extend service life and reduce CO2 emissions. Through this PhD scholarship, you will contribute
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, proteins, metabolites), aided by in silico target prediction, will enable us to uncover putative target of the compound, which will then be validated functionally using a broad range of biochemical and
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contribute to the development of predictive human in vitro models for ageing research while providing robust alternatives to animal experimentation. Where to apply Website https://emploi.cnrs.fr/Offres
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on temporal data (predictive maintenance, sensory processing for robot control, etc), in which efficient on-device processing is crucial. We are looking for a highly motivated PhD candidate with an interest in
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for a PhD fellowship in Predictive AI-Based Maintenance and Optimization of Building Energy Management Systems. aiD is one of the new Norwegian AI research initiatives, funded by the Research Council
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traffic demands increase, there is a growing need for innovative methods to continuously assess track condition and predict deterioration. This PhD project addresses this challenge by developing a novel