135 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" PhD positions in Norway
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- University of Bergen
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
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Field
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, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging scientific frontier. Duties of the position Fundamental contributions in embodied AI
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methods in forestry generate vast quantities of data and demand more accurate information. Machine learning allows for the systematization and processing of this data into new forms of information
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of current work processes. The project will adopt social science and sociotechnical perspectives such as computer supported collaborative work, HCI or organizational sociology to investigate the intra- and
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. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging scientific frontier
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the health services. Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/290397/phd-candidate-in-medicine… Requirements Research FieldMedical sciencesEducation LevelMaster Degree
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for forest applications Good presentation skills, written and oral Qualifications that will be emphasized Experience from research in boreal forest ecosystems Programming skills Experience with machine
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mixed models, permutational methods, Bayesian analyses, machine learning algorithms, structural equation modeling). A good practical knowledge of R Personal characteristics To complete a doctoral degree
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, Ocean Engineering, or similar. You must meet the requirements for admission to the faculty's Doctoral Programme https://www.ntnu.edu/iv/doctoral-programme Excellent written and oral English language
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this means that you must have more than 5 years of what is called higher education in your home country. Please confer the GSUlist for relevant information pertaining to your home country: https
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, currents, water levels, wind, and ice. Machine learning models will be developed to forecast future variations in such dynamic conditions and to incorporate the operational state of the vessel into routing