62 phd-in-computer-vision-and-machine-learning Fellowship positions at University of Oslo
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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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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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-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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. The position requires participation in the Faculty of Social Sciences' organised research education programme (PhD programme) and the completion of a doctorate in sociology or human geography. The candidate who
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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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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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candidate will be part of the Faculty’s PhD programme. The work is expected to lead to a PhD in political science. Required qualifications Formal qualifications Education equivalent to five years
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an advantage: applied microeconometrics and causal inference; machine learning and data science. Experience with one or more of the following computing skills will be considered an advantage: Natural
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-scale assessment data, meta-analyses of meta-analyses) Methods and approaches to cumulative, living, and community-augmented meta-analyses Methods and approaches to include machine learning and artificial