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for testing newly developed algorithms is anticipated in mainland Norway, Svalbard, and abroad. Funding is also available for conference attendances and research visits with external collaborators. The position
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on the development of machine learning algorithms, particularly transfer and adaptive learning, for multimodal wearable biosensing and its translation to rehabilitation and digital health applications. It is co
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. The project is supervised by Associate Professor Ulysse Côté-Allard at the Department of Technology Systems, University of Oslo, whose research focuses on the development of machine learning algorithms
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oncology through the development of allosteric drugs that target molecular machines essential for tumor genome reorganization. Utilizing our proprietary ALLOS platform, we identify and exploit the genetic
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cytosolic adapters modulate the phosphoproteome of T cells, using high end mass spectrometry approaches, as well as immunological and genetic techniques. The research fellow must take part in the faculty’s
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of genetic resources across land, oceans, jurisdictions, and global databases. It builds on a collaboration between the University of Oslo, Fridtjof Nansens Institute and the University College London, and it
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experience in the field in question Experience from ecology, bioarchaeology, palaeoecology or bioinformatic/working on genetic data Knowledge of cool-temperate ecosystems and particularly fish/aquatic systems
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. The interdisciplinary center integrates researchers with substantive expertise from sociology, psychology, education, economics, and genetics, and methodological expertise from educational measurement, psychometrics
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expertise from sociology, psychology, education, economics, and genetics, and methodological expertise from educational measurement, psychometrics, econometrics, statistics, and biostatistics. UiO/ Anders