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land use change is one of the largest perturbations to the global carbon cycle, so is an essential lever to limit climate change. However, predictions of how land use impacts climate remain highly
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“New predictive AI/ML solution applied to procurement and production management” (refª COMPETE2030-FEDER- 01474600), IN PROGRESS AT THE FACULTY OF ECONOMICS OF THE UNIVERSITY OF PORTO (FEP) The Faculty
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), for the project “New predictive AI/ML solution applied to procurement and production management” (refª COMPETE2030-FEDER- 01474600), IN PROGRESS AT THE FACULTY OF ECONOMICS OF THE UNIVERSITY OF PORTO (FEP
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), for the project “New predictive AI/ML solution applied to procurement and production management” (refª COMPETE2030-FEDER- 01474600), IN PROGRESS AT THE FACULTY OF ECONOMICS OF THE UNIVERSITY OF PORTO (FEP
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optimisation. State-of-the-art digital models and AI tools that incorporate machine learning could enable predictions of the dry fibre forming that are subsequently used as input into the RTM process model
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developing a suite of deployable tools and predictive models. These resources will enable Syensqo to identify optimal polymer film and prepreg chemistry combinations, facilitating the production of defect-free
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, experience and knowledge - In-depth knowledge of statistical mechanics, including the so-called 4th statistical ensemble - Experience in applying Monte Carlo numerical methods Essential skills and abilities
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to be developed within the framework of project “RheumaAID – AI-Enhanced Predictive and Proactive Care for Rheumatic and Musculoskeletal Diseases, with Notice No. Fundação para a Ciência e a Tecnologia 04
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Magalhães Mendes. Grant duration: Initial duration of 3 months, with the predicted starting date in December 2025, on an exclusive basis eventually renewable but never exceeding the end of the project
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
that describes this system through an analysis based on black hole perturbation theory. In a second phase, numerical computation of the results will be implemented to obtain quantitative predictions for different