177 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions in Norway
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to complete the final exam. Desired: Familiarity with statistical and machine learning techniques. Knowledge about molecular biology and/or gene regulation. Experience with nanopore sequencing, Hi-C, ribosome
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% teaching component. The Department teaches in all the sub-fields mentioned above. The successful candidate will be part of the Faculty’s PhD programme. The work is expected to lead to a PhD in political
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candidates will be admitted to the PhD program in Health and Medicine. The education includes relevant courses amounting to about six months of study, a dissertation based on independent research
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of the position is to complete research training to the level of a doctoral degree. Admission to the PhD programme is a prerequisite for employment, and the programme period starts on commencement of the position
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-tenured term of 4 years, and has a 25% teaching component. The Department teaches in all the sub-fields mentioned above. The successful candidate will be part of the Faculty’s PhD programme. The work is
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USN’s PhD-program in Technology within three months of accession in the position. About the PhD-project The build-up of CO2 in the earth’s atmosphere is recognized as the single most important
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Position as PhD Research Fellow in formal methods for data protection in digital twins is available at the Department of Informatics. Starting date no later than December 1, 2025. The fellowship period is
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three years with research duties exclusively. The hired candidate will be admitted to the PhD program in Social Sciences. The education includes relevant courses amounting to about six months of study, a
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commencement that the fellow is admitted to UiA's PhD program at the Faculty of Health and Sport Sciences, specializing in Health and Nursing Science. For questions about the PhD program, contact PhD-programme
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must participate in an approved educational programme for a PhD degree within a period of 4 years. The deadline for applying for admission to the PhD programme at The Faculty of Science and Technology is