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optimisation by supplying high-quality data needed to validate and refine the next generation of predictive numerical models. A key innovation in this research will be the use of transparent soil analogues
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time. In this project, we propose a method for identifying and classifying such emerging asynchronous trends. The goal is to be able to predict how a new emerging trend will develop using similar
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in fault detection, diagnostics (FDD), and preventative/predictive maintenance for industrial systems. The role is part of the EU-funded FLARE project, which focuses on improving industrial resilience
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, pharmacophore modelling, and molecular dynamics simulations to design novel GPR84 ligands with predictable signalling bias profiles. About the person: The successful candidate must have, and your application
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and edge computing; The design of architectures/models which accurately capture the complexities of the data, with robust estimates of confidence in predictions and compressed quantities of interest
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on the integration of BIM, artificial intelligence and predictive maintenance (PM) for intelligent BIM models, digital construction sites, predictive analysis and immersive interactions, outlining an operating
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, predictive analysis and immersive interactions, among others. Where to apply Website https://www.poliba.it/it Requirements Additional Information Eligibility criteria Eligible destination country/ies
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(2024) https://www.nature.com/articles/s41591-023-02702-z Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal. https://pmc.ncbi.nlm.nih.gov/articles
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numerical simulations, quantitative model/data comparisons, and exploration of predictive scenarios. Dissemination: Participate in the scientific promotion of results (publications, conferences). The position
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lightweight deep learning model for welding defect recognition. Weld. World. https://doi.org/10.1007/s40194-024-01759-9 J. Franke, F. Heinrich, R.T. Reisch, “Vision based process monitoring in wire arc additive