634 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" positions in Norway
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the Norwegian Institute for Nature Research (NINA) and partners in 14 countries. For more information, see: https://seatrack.net . This is a fixed termed position for 3 years in our section for terrestrial
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Energy and Environmental Economics, focusing on macroeconomic analysis of energy transition policies
in Norway. About the project This PhD position is part of the newly funded VISTA Centre for Norwegian Transformative Energy Policy Development (NOTRAP) (https://www.ntnu.edu/notrap ), which will
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an international and interactive environment. Candidates must have extensive experience with: Programming (including MATLAB) and computational modelling Machine Learning (ML) methodology applied for complex data
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learn how to write a successful MSCA-PF application. The selected candidates will, jointly with the supervisor, write the MSCA-PF application by the deadline of September 9, 2026. In this call we search
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health, epidemiology, statistics, biostatistics, or machine learning/artificial intelligence. You must have a strong academic background from your previous studies and have an average grade from your
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at uit.no/project/arcticmsca/program-structure ). At this event, the candidates will present their past research achievements, discuss future plans with their potential supervisor and learn how to write a
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plays in society and how professional language functions, is learned, and used in different contexts. Participants in work package 2 will study how professional language is used in education, research
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Interaction (HCI). The position will collaborate closely with (1) the NTNU Shore Control Lab (SCL), a design and human factors research environment focusing on human-centered design of technology for safety
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about working and living in Norway can be found here: https://uit.no/staffmobility Application Please note that the application will only be assessed based on the information submitted by the application
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-year master’s degree, with a learning outcome corresponding to the descriptions in the Norwegian Qualification Framework, second cycle. The applicant must have a documented strong academic background