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analyses related to the experiments (statistics, programming, interpretation of microbiota data from e.g. 16S rRNA gene sequencing) The successful candidate is expected to engage into a progress plan for a
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or retain water. Our Faculty is involved in developing knowledge in this subject via domestic and international collaborative projects, using experimental data collection, statistical learning and numerical
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of evapotranspiration using remotely sensed data and climate data. Statistical- and scenario analyses addressing impacts of treeline expansion on runoff. Write and publish scientific papers. The successful candidate is
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gamma-radiation), mass spectrometry analysis or with X-ray based analytical methods. Experience with programming and data analysis, including applied statistics. You need to have: Strong scientific
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and motivation for the position. The following experiences and skills will be emphasized: Strong background in statistical physics and electrodynamics Strong skills in mathematics and analytical
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systems Strong skills in data analytics, statistics and/or machine learning techniques. Skills in scientific writing The applicant's estimated academic and personal ability to complete the project within