38 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" positions in Italy
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sustainability. The selected researcher will contribute to the development of predictive models and machine learning algorithms for data analysis from plant-based sensors, multispectral and thermal imagery, and
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Research Framework Programme? Horizon 2020 Is the Job related to staff position within a Research Infrastructure? No Offer Description Machine learning for gravitational waves, LISA data analysis Where
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, funded by FAR 2024 UNIMORE linea FOMO, and aims to develop authenticity models through environmentally friendly analytical techniques combined with data processing and machine learning algorithms
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of Pisa) and Dr. Stan Van Gisbergen (SCM, Holland) https://www.scm.com/ , who will also serve as industrial mentor. DC9 - Objectives: Apply Machine Learning force fields and sampling methods to model bio
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. Through continuous structural monitoring systems Through continuous structural monitoring systems and artificial intelligence algorithms (machine and deep learning, hybrid physical-data driven methods
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This research focuses on developing and validating Big Data-driven machine
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materials according to the Lambert–Beer law, thus enabling an accurate description of PEC device behavior. In parallel, the coupling between kMC and CFD simulations will be achieved through machine learning
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, early detection of degradation, and residual life prediction. The program integrates physical modeling, machine learning, and data fusion techniques to optimize predictive maintenance, reduce operating
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include: (1) implementing light–matter interaction in CFD via the radiation transport equation and suitable attenuation models; (2) integrating kMC-based surface kinetics through machine-learning surrogate
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Description REALISE - Bridging Igneous Petrology and Machine Learning for Science and Society About the REALISE Doctoral Network REALISE will train 15 Doctoral Candidates at the interface of igneous petrology