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- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
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machine learning, e.g. predicting rate of penetration (ROP) and wear. Investigate the possibilities in automation and robotization and the use of artificial intelligence. Electric drilling and other methods
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to valuable learning experiences and opportunities for co-authorship. The extent and type of involvement will be tailored to the candidate’s background and determined in consultation with the supervisory team
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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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Norwegian University of Science and Technology (NTNU) for general criteria for the position. Personal characteristics Ability to work independently and in a team Drive to learn new methods and applications
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patients Experience with clinical data collection Familiarity with epidemiological methods and registry-based research, epigenetic analyses or machine learning. Interest or experience in science
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registry-based research, epigenetic analyses or machine learning. Interest or experience in science communication and public engagement Experience with publishing biomedical papers Experience with open
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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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. 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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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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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 employees, of which 50 are permanent