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machine learning and/or image analysis/computer vision A solid and documented background in machine learning, mathematics, linear algebra, and/or statistics Documented knowledge and experience in Python
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can also be considered given that the candidate has formal competence in machine learning and/or image analysis/computer vision A solid and documented background in machine learning, mathematics, linear
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thesis being approved. In the evaluation of the applications, emphasis will be placed on: The research project’s scientific merit, research-related relevance and innovation The applicant’s estimated
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The net uptake of carbon to terrestrial systems (LULUCF) in Norway is estimated to be 20-25 MtCO2e/yr or about 50% of the anthropogenic greenhouse gas emissions. However, the positive trend in the estimated
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contemporary streaming data scenarios, such as evolving baselines and complex, data-intensive settings. The applicant must master theoretical work in the field of change and anomaly detection and estimation, as
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Fellowship at the University of Oslo. Project description The net uptake of carbon to terrestrial systems (LULUCF) in Norway is estimated to be 20-25 MtCO2e/yr or about 50% of the anthropogenic greenhouse gas