156 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions in Norway
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computing facilities. • A stimulating research environment with strong support for professional and academic development. • A strong support system available for PhD candidates, including access to wide
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(PhD programme) and the completion of a doctorate in sociology or human geography. The candidate who is hired will automatically be admitted to the PhD programme. Residence in Norway is expected, but PhD
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-driven to advance with their research project. Work in an interdisciplinary team with expertise in mechanics, complex fluids, physics and biophysics and sustainability thinking. Follow our PhD program that
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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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(PhD programme) and the completion of a doctorate in sociology or human geography. The candidate who is hired will automatically be admitted to the PhD programme. Residence in Norway is expected, but PhD
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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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Econometrics Virtual power plants Power systems and/or power electronics Machine learning Renewable energy systems Advanced statistics Language requirement: Good oral and written communication skills in English
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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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, 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 expected to lead to a