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- NTNU Norwegian University of Science and Technology
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- OsloMet – Oslo Metropolitan University
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inference methods, survey design, and/or machine learning Experience with web scraping and API-based data collection Organizational and coordination skills, such as assisting in drafting terms of reference
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including, high resolution 3D and 2D seismic, sub-bottom profiler, regional 2D seismic and petrophysical logs; infer complex Earth system process understanding, including changes in current patterns, glacial
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of past warm periods in diverse geophysical datasets including, high resolution 3D and 2D seismic, sub-bottom profiler, regional 2D seismic and petrophysical logs; infer complex Earth system process
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specialisation The Department of Business and Management Science is responsible for a specialisation in the NHH PhD programme. If admitted, the candidates will follow the Business Economics track
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psychology, neuroscience, AI engineering, human-computer interaction, and social science, with lifespan perspectives. Using advanced methodologies like neuroimaging, eye-tracking, virtual reality, and neural
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qualifications: Strong programming skills Experience with handling large data sets Experience with high-performance computing Familiarity with Earth System Models in general, and NorESM in particular Strong track
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postdoctoral researcher, you will investigate how contextual factors affect children’s executive function engagement, using neuroscientific methods such as eye-tracking, pupillometry, and EEG. The project has
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for reducing pressures on species moving and migrating between conservation areas. The work will be based on existing GPS tracking and survey data on highly mobile and migratory species of seabirds, fish and
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high-performance computing Familiarity with Earth System Models in general, and NorESM in particular Strong track record of relevant peer reviewed publications All candidates and projects will have to
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and marine protected areas for reducing pressures on species moving and migrating between conservation areas. The work will be based on existing GPS tracking and survey data on highly mobile and