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- NTNU - Norwegian University of Science and Technology
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and popular science dissemination Participate in international activities such as conferences and/or research stays at foreign educational institutions Teaching (optional but recommended, learning
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NMBU. The applicant must have an academically relevant education corresponding to a five-year master’s degree, with a learning outcome corresponding to the descriptions in the Norwegian Qualification
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”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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programmes at bachelor’s and master’s level. Some of the best lecturers in Norway are amongst our employees, and we are proud of our prizewinning teaching and learning environment. The Department has 200
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program development, partnerships between educational institutions and other stakeholders, and the impact of higher VET on career pathways and lifelong learning. Required selection criteria You must have a
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. The successful candidate will acquire broad training in the necessary research skills, and the position will suit a candidate who is motivated to undertake high-level research in the interface between different
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-minded, well organized, looking forward to learning and developing new techniques and has good communication skills. Employment in the position is based on a comprehensive assessment of all qualification
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the PhD candidate may include (non-)linear inverse load estimation and data-driven/machine learning techniques that rely on physics-informed guidance for improved robustness. A key task will be to quantify
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teach mechanical engineering, engineering and ICT, and civil and environmental engineering. The Department conducts internationally leading research and participates in several large national research
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the interaction between digitalisation and society from various theoretical perspectives and develop new responsible digital technology. Our other priority area of research is Language in Learning, which aims