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to machine learning. This PhD provides a unique opportunity to shape emerging concepts in Artificial Intelligence Informed Mechanics (AIIM), combining fundamental research with methodological innovation. You
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. You will explore how emerging AI technologies—foundation models, generative design tools, agent platforms, reasoning engines, and reinforcement learning—can be adapted and extended for maritime design
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1Geofield Contact City Trondheim Website http://www.ntnu.no Street Høgskoleringen 1 Postal Code 7491 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo
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interconnected Internet-of-Energy (IoE) ecosystems. In this context, the MSCA Doctoral Network project SAILING (https://Secure AI and Digital Twin Empowered Smart Internet-of-Energy ) aims to establish a
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activities Engage in international activities such as conferences and/or undertake research stays at foreign educational institutions Teaching and supporting of learning activities in courses related
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Code2815StreetTeknologivegen 22Geofield Contact City Gjøvik Website http://www.ntnu.no Street Teknologivegen 22 Postal Code 2815 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket
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document that you are particularly suitable for a PhD education. You must meet the requirements for admission to the doctoral program from the Faculty of Engineering (https://www.ntnu.edu/studies/phiv ) You
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, especially large language models (LLMs), enable the development of interactive AI agents that can support human learning in complex, safety-critical environments. Human-centered AI in this project means
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candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable implementations. By establishing a new class of multi-frame factorization methods
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learning, can guide self-healing decisions in a way that reduces downtime without inducing oscillation or cascading secondary failures. The research focus is hands-on and systems-oriented: the candidate will