20 phd-studenship-in-computer-vision-and-machine-learning PhD positions at University of Bergen
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democracy, our centre tackles the promise and peril of hybrid intelligence—humans and machines working and learning together. Our mission is to establish an internationally leading interdisciplinary hub
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PhD position at the Faculty of Law (AI LEARN) Apply for this job See advertisement UiB - Knowledge that shapes society UiB shall be among Europe's leading universities, internationally recognized
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17th December 2025 Languages English English English PhD position at the Faculty of Law (AI LEARN) Apply for this job See advertisement UiB - Knowledge that shapes society UiB shall be among
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that they have received your application. Please note that the automatic recognition offered by HK-dir is not sufficient, and will not be accepted as basis for admission to the PhD programme. Applicants with
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application. Please note that the automatic recognition offered by HK-dir insufficient and will not be accepted as basis for admission to the PhD programme. Applicants with education from a Nordic country or
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, phylogenetics, species delimitation and other analyses, as well as writing up. The PhD candidate must take part in the University’s approved PhD program leading to the degree within a time limit of 4 years. Hence
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insufficient and will not be accepted as basis for admission to the PhD programme. Applicants with education from a Nordic country or those with a medical degree from the EEA area and a license to practice
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-ranked international journals. Qualifications and personal qualities: Applicants must hold a degree equivalent to a Norwegian doctoral degree (PhD) within engineering, informatics, energy, mathematics
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PhD program leading to the degree within a time limit of 4 years. Hence, applicants must meet the formal admission requirements for the PhD program. Application for admission to the PhD study, including
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epidemiology, causal inference, genetic epidemiology, and machine learning. As a PhD candidate in the project, you will: Actively participate in group meetings, design statistical analysis plans in collaboration