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within the “Artificial Intelligence for Polarized Fusion” project Where to apply Website https://pica.cineca.it/uniroma2/ Requirements Additional Information Eligibility criteria Eligible destination
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Università degli Studi di Roma Tor Vergata - Dipartimento di Scienze Chirurgiche | Italy | 29 days ago
project aims to develop and train an artificial intelligence–based multiplex network for individualised risk stratification in prostate cancer. By integrating genomic, transcriptomic, clinical, pathological
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George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș | Romania | 18 days ago
. Clin. Med.,2025, 14(19):6752. https://doi.org/10.3390/jcm14196752 Khalifa, M., Albadawy, M. Artificial Intelligence for Clinical Prediction: Exploring Key Domains and Essential Functions, Computer
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comprehensive knowledge graph for SSH and integrating applications based on artificial intelligence and large language models, GRAPHIA will convert heterogeneous SSH data into more interoperable and machine
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performance and remaining useful life prognostics, combining experimental data with physics-based and statistical models. A key role is played by Artificial Intelligence and Machine Learning techniques
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second in the UK for research power and first in England. About the role The project will be carried out at the Department of Computer Science, in the Machine Intelligence Lab (https
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are encouraged to visit the ESA website: http://www.esa.int Field(s) of activity for the internship Topic of the internship: Artificial Intelligence / Machine Learning for ECSS space standards requirements
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Information Work Location(s) Number of offers available2Company/InstituteThe Italian Institute of Artificial Intelligence (AI4I)CountryItalyState/ProvinceToCityTurinGeofield Contact City Torino Website https
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imaging, social computing, and AI hardware. CASIA is the first national research institution to carry out brain-inspired intelligence research in China. CASIA also established the first School of Artificial
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the production deployment of the solution on an arthroscopy column; - Evaluate and validate the model during the different phases of the process. Advances in Artificial Intelligence now make it possible