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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
quality. Secondly, different machine learning strategies based on traditional supervised learning techniques (e. g. random forest (RF), artificial neural network (ANN)) will be applied using the parameters
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of external conditions. Recent work has demonstrated the strong potential of combining Internet of Things (IoT) devices with artificial intelligence in the cloud, but to date no solution has proposed embedding
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using headturn-preference experiments. In this research programme, you work in an interdisciplinary team with researchers from the fields of linguistics, psychology, and artificial intelligence. You
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
mechanics, and artificial intelligence (AI)—specifically in the domains of non-destructive evaluation (NDE), computer vision, and machine learning. It addresses a critical challenge in the structural health
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for Artificial Intelligence are set to launch in the fall of 2025. These centers will foster interdisciplinary collaboration among researchers to address societal challenges, understand the impact of AI, develop
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outside academia. This PhD fellowship is part of the newly established AI Centre for the Empowerment of Human Learning (AI LEARN) .Six national research centers for Artificial Intelligence are set to launch
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Artificial Intelligence.” The project aims to develop and empirically validate a taxonomy of non-ordinary states of consciousness (NOS) using artificial intelligence and language technology methods. The focus
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looking for a full-time (100%) doctoral scholarship holder in the field of artificial intelligence. The research of this PhD position will be conducted in the IDLab research group , which is embedded in
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Advanced Manufacturing, Artificial Intelligence, and Materials Design under the STAR (Space Technologies and AI-Driven Research) Frontier initiative. These positions are housed within the Aerospace Center
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the feasibility of novel ultralow-power electronics based on quantum-mechanical tunnelling processes in advanced CMOS, which has a strong potential for Internet-of-Things devices and edge-artificial intelligence