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Opportunities to work with exciting research tasks and expand your network together with NORCE Interdisciplinary work in and across teams Good opportunities for professional and personal development in
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networks financed by European and Norwegian research funding institutions. More information about ARENA is available at www.arena.uio.no . Project description The WAGE project is a comparative, multi-level
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network, and will be given the opportunity to work with researchers across the world. For more information: Democracy, Children and Representation - Department of Education and Humanities Studies in
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for applicants with: a strong interest and expertise in computer science research with a focus on machine learning methods for the health domain strong coding skills familiarity with state-of-the-art machine
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research themes at the forefront of modern science A friendly, inclusive, and collaborative international working environment that values diverse perspectives Access to a strong network of top-level national
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. Graph Neural Networks (GNNs) are very successful for learning on KGs and solving the mentioned tasks, but also have great potential for incorporating symbolic knowledge due to strong connections between
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background and interest for coding scientific software is required. Your course of study must correspond to a five-year Norwegian course, where 120 credits have been obtained at master's level. Master students
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and reproducible research, e.g., in the development of codes and algorithms. We will focus on devising computational solutions that can immediately be of use in other applications contexts as well
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as well as PhD fellows, participation in departmental and university-wide activities, attract external research funding, and establish national and international collaborative networks. Main tasks will
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manuscripts based on findings, targeting publication in peer-reviewed journals and dissemination of results within partner networks Thesis Writing: Compile research outcomes and manuscripts into a cohesive