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, Physics, Electrical Engineering, Communication Engineering, or equivalents; – Knowledge in artificial intelligence, statistical and machine learning, complex systems, agent-based modeling and simulation
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archaeologists to understand AI results – Generalization and transferability analyses, considering domain adaptation and transfer learning strategies to ensure model robustness across different geographic regions
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process data locally while ensuring efficient and scalable artificial intelligence at the edge. TinyML and Edge AI have demonstrated the feasibility of embedding machine learning models on such devices
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). Desirable assets are: • Machine learning, deep-learning, artificial intelligence, advanced statistical inference; • A solid record of research activities, including relevant publications in international peer
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, modelling, or computer-aided design (CAD) skills Specific Requirements Compliance with the MSCA Doctoral Network mobility rule Must not have a doctoral degree at the date of their recruitment Willingness
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assurance, data science, data-driven modelling, digital manufacturing workflows, and Digital Product Passport B.3 Hands-on experience in machine learning, ontologies and knowledge graphs, IIoT and digital