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Field
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artificial intelligence (AI), it is now possible to generate realistic synthetic images, offering an ethical and scalable way to expand healthy tissue collections and support future research. This project will
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on mechanistic study of high cor
of structural lightweight construction, energy research and medical technology. The experimental development is closely accompanied by modelling approaches and artificial intelligence methods. Interested? Please
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One fully funded, full-time PhD position to work with Alessandro Suglia in the Embodied, Situated, and Grounded Intelligence (ESGI) group at the School of Informatics, University of Edinburgh
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/funding reference: TSI-100925-2023-1 Component 16 of the Recovery, Transformation and Resilience Plan. National Strategy for Artificial Intelligence. ENIA's strategic axis 2 of action "Promoting
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/funding reference: TSI-100925-2023-1 Component 16 of the Recovery, Transformation and Resilience Plan. National Strategy for Artificial Intelligence. ENIA's strategic axis 2 of action "Promoting
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of structural lightweight construction, energy research and medical technology. The experimental development is closely accompanied by modelling approaches and artificial intelligence methods. Interested? Please
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experience related to the position in artificial intelligence application programming and network programming (punctuation: 35) Item 04: Specific education related to the position, see previous point
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Are you passionate about developing intelligent algorithms that can support repair and remanufacturing decisions for sustainable manufacturing? As a PhD researcher, you will create innovative
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FUNDED BY THE UPV'S RESEARCH STRUCTURES – SUBPROGRAMME 2 (PAID-01-22) 116329 Completion of a doctoral thesis on manufacturing process optimization through the implementation of Artificial Intelligence
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University, is recognized for its expertise in artificial intelligence and formal methods In this stimulating academic context, we will focus on the problem of explainability of artificial intelligence models