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using radiomic imaging algorithm in Hypoxic Ischaemic Encephalopathy). The Sophie project aims to develop a Neonatal MRI Biomarker for newborns with Hypoxic Ischaemic encephalopathy that is predictive
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. The QUBIC consortium will deliver disruptive innovations across three core quantum domains: Development of quantum algorithms to solve current industry-specific challenges. Advancement of quantum processors
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) approaches. Design predictive maintenance algorithms using machine learning, statistical learning, and digital twin-based models to anticipate failures and optimise maintenance interventions. Integrate AI
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modern genetic datasets and functional genetics now available to trace the evolutionary history of production and sustainability traits over 10,000 years. Using selection analyses, the research will
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passionate about applying ML algorithms and developing AI applied research and innovation solutions using classic ML to novel transformer neural networks. We test and measure the real customer impact of each
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and to better understand the physiological mechanisms of resistance to abiotic constraints. The acoustic signature, integrated into the algorithm controlling the autonomous acoustic sensors, will
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technical knowledge in areas such as: Foundational Models Algorithmic Research Machine and Deep Learning Computer Vision Edge AI, TinyML, and Embedded AI Explainable AI Safe AI Federated, Parallel