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to demonstrate skills on Data Analytics and Machine Learning, in particular on distributed ML. Must have very good programming competence in Python, Java, C/C++ or equivalent Fluent oral and written communication
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project “Actively learning experimental de-signs in terrestrial climate science (ACTIVATE)”: https://www.mn.uio.no/geo/english/research/projects/activate/index.html The PhD fellow will be part of a growing
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Documented Python programming skills Desired qualifications: Experience with change point detection and anomaly detection Relevant experience with data from the maritime sector Language requirement: Good oral
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scientific computing, for example Python Candidates without a master’s degree have until 1 October 2026 to complete the final exam. Desired qualifications: The following qualifications are considered strongly
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datasets metabolomics or analytical chemistry microbial community analysis programming/scripting in R, Python, or similar languages systems biology or computational biology Knowledge of a Scandinavian
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ML. Must have very good programming competence in Python, Java, C/C++ or equivalent Fluent oral and written communication skills in English Desired qualifications: Publications in reputed journals and
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before the starting date Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system Have programming experience in Python, specifically
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is part of the ERC-funded project “Actively learning experimental de-signs in terrestrial climate science (ACTIVATE)”: https://www.mn.uio.no/geo/english/research/projects/activate/index.html The PhD
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Documented knowledge of statistical theory and methods and core machine learning methods Documented Python programming skills Desired qualifications: Experience with change point detection and anomaly
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collaborators. The position is part of the ERC Starting Grant “Actively learning experimental designs in terrestrial climate science (ACTIVATE)”: https://www.mn.uio.no/geo/english/research/projects/activate