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for Horticulture and Phenotyping) team research topics focus on low cost computer vision and machine learning, simulation assisted plant phenotyping and machine learning based data mining for plant biology
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guaranteed. Given the real-time nature of these large complex infrastructures, machine learning techniques can complement more deterministic algorithms to guarantee a reliable operation of the system
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should possess a strong background in advanced computing and data science, machine learning, or in a related field, with expertise in monitoring data reliability, quality assurance, and AI modelling
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Predictive Maintenance: employing big data analytics to assess ballast degradation and particle morphology, supported by machine learning algorithms. Data-Driven Numerical modelling Simulations: leveraging
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concrete affected by internal expansion reactions. The main tasks to be accomplished are: • Acquire knowledge about the expansive phenomena and their modelling, considering the thermo-hygrometric