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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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, privacy concerns and more. The UiT team will collaborate with the other research teams within the TRUSTING consortium. The Health Data Lab (HDL) is a research group at the Department of Computer Science
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Machine Learning is available in the Department of Informatics and the Norwegian Centre of Excellence Integreat . Starting date as soon as possible and upon individual agreement. The fellowship period is
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university department for general education and research in Computer Science and related topics. The Department has more than 1800 students on bachelor level, 600 master students, and over 240 PhDs and
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of Informatics, Uni-versity of Oslo, and will be part of a growing research agenda at the intersection of epidemiology, statistical modeling, machine learning and public health data systems. The project aligns
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degree or currently working on finalizing master thesis in computer science, statistics, mathematics, data science, or related fields. Strong background in statistics and linear algebra. Foreign completed
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advertisement About the position Position as Postdoctoral Research Fellow available in Machine Learning is available in the Department of Informatics and the Norwegian Centre of Excellence Integreat . Starting
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(SCML) group at the Department of Informatics. The candidate will be part of and contribute to the research activities in the Climate Health project at the HISP Centre. Starting date as soon as possible
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the main supervisor Kari Ingstad at kari.ingstad@nord.no . Employment in the position requires an application for admission to the PhD in professional science at the Faculty of Nursing and Health Sciences
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security, privacy concerns and more. Working environment The Health Data Lab (HDL) is a research group at the Department of Computer Science at UiT - The Arctic University of Norway. HDL’s mission is to