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for data processing and analysis will be used. The fellow will also take part in modeling and simulation activities, as well as in the dissemination of results. Specific tasks include: A2. Data Collection
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their chemical structure and composition through structure–processing–property correlation analysis and model-based optimization of processing parameters. Leveraging these methods, we will demonstrate
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The Computer Vision-Core Artificial Intelligence Research (Vision-CAIR ) group led by Prof. Mohamed Elhoseiny at the CS Program of the King Abdullah University of Science and Technology (KAUST) is
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machine learning, big-data analytics, and data-driven approaches to optimise composition–process–property relationships. Key responsibilities will include: Research: Conduct additive manufacturing research
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18 Mar 2026 Job Information Organisation/Company FEUP Department Human Resources Division Research Field Engineering » Electrical engineering Engineering » Computer engineering Engineering » Other
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the complexity further to effectively plan their movement and deployment. Existing methods rely on fixed data and static models, which struggle to adapt to real-time changes and unpredictable conditions. This
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fracture model to predict the macroscopic fracture energy from the bond-level dissipation and failure mechanisms experimentally observed in the process-zone. 4.Planned secondments Secondments will be decided
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. Existing methods rely on fixed data and static models, which struggle to adapt to real-time changes and unpredictable conditions. This limits the ability to optimize energy storage use for critical
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on increasing variability and extreme events in watersheds. Expand knowledge of process-based modeling approaches to assess relationships between forest species composition, biomass, and water yield Develop
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)for a master (the location may take place locally, hybrid or abroad depending on the work plan) for the project “DRYAD (DEMONSTRATION AND MODELLING OF NATURE-BASED-SOLUTIONS TO ENHANCE THE RESILIENCE