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between Numerical Analysis and Machine Learning, with a focus on physics-informed machine learning. The goal is to design learning strategies that embed the structure of governing physical laws, enabling
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conducted in English, the following knowledge will be verified (maximum 65 points): Programming skills (Python, R, or equivalent) (maximum 20 points); Artificial intelligence, machine learning, and/or large
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for Physics-Informed Statistical Learning for applications to real data problems of sustainable development. Regression models capable to integrate the available data with the a-priori knowledge derived from
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of the elasticity parameters observed on real examples, iv) coordination of the activities with the other project members. Where to apply Website https://www.univr.it/it/concorsi/contratti-e-assegni-di-ricerca
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Learning methods for modeling spatial and spatio-temporal data, including point pattern data, possibly observed over complex domains. The candidate will specifically consider physics-informed statistical
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Research Infrastructure? No Offer Description The requested figure will be responsible for developing and implementing both machine-learning methods for analysing images and audio files in Python, as
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Study and development of monitoring and prediction services for critical components of machine tools
conducted in close collaboration with Pama SpA (https://pamamachinetools.com/ ), an Italian company with over 90 years of experience in the machine tool market... Where to apply Website https
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The research activity will focus on the development of algorithms for machine
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Electrification on environmental impact reduction of tomatoes harvesting machines
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of deep neural networks in the field of adaptive processing of graph data (Deep Graph Learning) . The developed novel approaches will be applied to case studies in bioinformatics Requirements Additional