66 machine-learning-"https:"-"https:"-"https:"-"UCL"-"UCL" Fellowship positions in Norway
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measurement quality issues related to respondent non-compliance in ecological momentary assessment or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models
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completed a doctoral degree in (machine learning, statistics, or similar). You must have a professionally relevant background in algorithms, machine learning, database systems, or data mining. Experience with
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research. Potential topics include addressing measurement quality issues related to respondent non-compliance in ecological momentary assessment or exploring the use of machine learning techniques to aid
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level, developing and employing machine-learning tools for predicting antibody-epitope binding. In silico antibody design is a long-standing computational and immunological problem. Improving
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influencing their lives. This call requests research proposals that employ a practice-based programmatic research-through-design methodology, evolving learnings through oscillation between practice-based design
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participation in the war in Myanmar since the 2021 military coup d’état. This responsibility includes a mapping of the conflict’s digital war ecology and focusing in on a specific example of remote participation
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the competencies that the Research Fellow will acquire. Access to career guidance will be provided throughout the doctoral education. Research topic Over the past years, University of Stavanger has acquired strong
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to build up a researcher profile and competence that qualifies the person to apply for a position as associate professor. The postdoctoral researcher will focus on the work package 'Learning, economic policy
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have experience with applications of machine learning and deep learning on medical image data that you have experience applying methods within generative artificial intelligence to medical images and
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. The position is based at the Department of Informatics, University of Oslo, and will be part of a growing research agenda at the intersection of geographic information systems, epidemiology, machine learning and