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- NTNU Norwegian University of Science and Technology
- NTNU - Norwegian University of Science and Technology
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-health-economics-and-obesity Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/293904/phd-candidate-in-health-e… Requirements Research FieldMedical sciencesEducation LevelMaster Degree
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to SAFE. Delivering EVU course from SAFE center. Required selection criteria A PhD degree (or equivalent) in biometrics, information security, computer science, electrical engineering, or machine learning
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position Distributed machine learning takes advantage of communication and
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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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, 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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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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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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to evaluate and inform digital health interventions for women at increased risk of GDM. The project will primarily utilize data collected from a completed randomized controlled trial (https://bump2babyandme.org
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Code7491StreetHøgskoleringen 1Geofield Contact City Trondheim Website http://www.ntnu.no Street Hogskoleringen 1 N-7491 Postal Code 7491 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail
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to evaluate and inform digital health interventions for women at increased risk of GDM. The project will primarily utilize data collected from a completed randomized controlled trial (https://bump2babyandme.org