204 computer-security "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "St" PhD scholarships in Norway
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lab with access to specialized equipment such as a P2 solo instrument which will be used to perform Oxford Nanopore Sequencing on site. We also have access to computational clusters which can be used
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" Apply for this job See advertisement The position A PhD position is available at the Department of Technology and Safety (ITS), Faculty of Science and Technology with the research group Advanced
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, there is a pull for growth, increased efficiency and profitability, while managing volatility in the markets. Moreover, the sector is critically important for global supply chains and security in a tense
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gain admission to the PhD programme in (https://www.ntnu.edu/studies/phkjpros) within three months of your employment contract start date, and that you participate in an organized doctoral programme
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the requirements for admission to the faculty's doctoral program (see: https://www.ntnu.edu/ie/research/phd ). You must meet the requirements for admission to the IE Faculty. PLEASE NOTE: For detailed
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. You must meet the requirements for admission to the faculty's doctoral program (see: https://www.ntnu.edu/ie/research/phd ). You must meet the requirements for admission to the IE Faculty. PLEASE NOTE
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. Kai Sandvold at the Department of Chemistry and Biomedical Science, NTNU as well as the clinical academic group for multiple myeloma research at NTNU and St. Olav’s University Hospital. The position is
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research disciplines. For further information about the different research disciplines see https://www.ntnu.edu/imf/research . Are you motivated to take a step towards a doctorate and open exciting career
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syndrome (PCOS) who have participated in different clinical studies based at NTNU/St. Olavs hospital since the early 2000s. Data from the HUNT4 Survey (the fourth survey of the Trøndelag Health Study) will
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Digital Twin for façade condition, fire safety risk classification, and maintenance planning Apply statistical and machine-learning methods to link climatic loads to degradation indicators Validate models