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develops efficient and robust algorithms for realistic settings in terms of data and computing resources and collaborates to address major challenges in important applications including marine domain and
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if such requests are not allowed. Contact information For more information about the position, please contact: Prof. Salman Nazir: salman.nazir@usn.no Head of department Tor-Inge Myklebust Lie: tor-inge.lie@usn.no
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mathematical modelling tools. Excellent knowledge of programming languages such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in
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For further information please contact: Prof. Helge Hellevang +47 90 61 35 26 helghe@geo.uio.no or Dr. Mohammad Nooraiepour mohammad.nooraiepour@geo.uio.no For questions regarding Jobbnorge, please contact HR
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interdisciplinary, international project with partners in Norway, Austria and the USA. The successful candidate will work in the group of the project leader, Prof. Mathias Ziegler, at the Department of Biomedicine
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technological progress in our increasingly digital, data-driven world. Researchers in Integreat develop theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data. By
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develops efficient and robust algorithms for realistic settings in terms of data and computing resources and collaborates to address major challenges in important applications including marine domain and
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the real world. The candidate further develops efficient and robust algorithms for realistic settings in terms of data and computing resources and collaborates to address major challenges in important
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at the Department). The PhD-project will be connected to the research group of Prof. Nathalie Reuter at the Department of Chemistry and the Computational Biology Unit , in collaboration with Prof. Odd André Karlsen
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with AI algorithms and Machine Learning Fluent oral and written communication skills in English Desired qualifications: Experience with research on epidemiological modelling, with an emphasis on zoonotic