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? Generative AI and large-language models (LLMs) are about to turn computer-aided engineering into true human–AI co-design. In the new MSCA Doctoral Network GenAIDE we team up with Honda Research Institute
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) Project Why apply? Generative AI and large-language models (LLMs) are about to turn computer-aided engineering into true human–AI co-design. In the new MSCA Doctoral Network GenAIDE we team up with Honda
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. Analytical skills, initiative and creativity are highly desired. You are a naturally curious person who is eager to learn more and has a strong interest in research. Excellent written and oral communication
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creativity are highly desired. You are a naturally curious person who is eager to learn more and has a strong interest in research. Excellent written and oral communication skills in English are a prerequisite
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Why apply? Generative AI and large-language models (LLMs) are about to turn computer-aided engineering into true human–AI co-design. In the new MSCA Doctoral Network GenAIDE we team up with Honda
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) at the Faculty of Law and the Jantina Tammes School of Digital Society, Technology and AI research community. The supervision of the researcher will be jointly carried out between profs Jeanne Mifsud Bonnici
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description This project addresses the effective design of a military supply logistics network, composed of transportation and communication links such as roads and rail, aerial drone routes, and nodes, such as
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discourse moments, as well as interviews reconstructing first-person experiences and social networks. The project scrutinizes the blurred boundaries and competing aims we now see between journalism, as a
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or dairy farming Solid experience in project and programme management An excellent external network (both national and international) Strong command of both Dutch and English As we operate in an increasingly
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-thermal and geothermal heat sources and waste heat recovery (e.g., industrial waste heat reuse, sewage treatment plant) as components in a 5th generation district heating network. The key weakness of most