190 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" scholarships in Norway
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- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
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- NORWEGIAN UNIVERSITY OF SCIENCE & TECHNOLOGY - NTNU
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resulting precipitation and extreme weather. We study global and regional climate change and are at the core of international community climate modeling efforts that also involve AI and Machine Learning. We
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energy applications. You must have experience with data analysis, machine learning, or AI-supported methods applied to engineering or safety problems. PLEASE NOTE: For detailed information about what the
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towards the public healthcare system, and the potential consequences for health inequality and health policy conflicts. Through the project, you will acquire practical skills in survey methods and
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acquire. Access to career guidance will be provided throughout the doctoral education. Research topic The PhD Fellow will be affiliated with the research group FLUENT (FLerspråklig Utvikling og Endring i
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, you can expect: An attractive and supporting learning environment Participation in research groups Close supervision Skilled supervisors Excellent job prospects The programme is administered by
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for three years with research duties exclusively. A career plan will be prepared that specifies the competencies that the Research Fellow will acquire. Access to career guidance will be provided
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for admission to a PhD programme at 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
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acquire. Access to career guidance will be provided throughout the doctoral education. Research topic LISA is the forthcoming ESA-led mission designed to measure gravitational waves in the millihertz
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. The project will contribute to research within human–computer interaction and human factors on topics including: human–AI teaming in safety-critical work AI transparency and explain-ability in operational
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to design and evaluate Artificial Intelligent (AI) systems with and for people, aligning AI technologies with human needs and values, situated at the intersection of AI and Human-Computer Interaction