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to Danish data sources (e.g., registry data, surveys, and organisations). Your competencies Digital methods such as machine learning based classification, computational text analysis, network
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experiments. Multiplex cytokine and biomarker quantification. Western blotting and molecular immunology techniques. Bulk RNA-seq (and scRNA-seq) data analysis. Desirable: R/Python-based bioinformatics. As a
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. You will be responsible for all data analysis. You will report to the Head of Department of Biomedicine. Your competences Successful candidates will have an excellent track record and will be highly
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. Experience with one or more of the following would be an advantage: marine sedimentology and sediment-core analysis, geochronology, Greenland glaciology, statistical analysis of proxy data. You should have
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interpretation of proxy records, quantitative analysis of environmental data and integration of geological archives with knowledge of modern Arctic climate and oceanography. Who are you? You have a MSc degree
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assimilation, (3) satellite geodetic and/or Earth Observation (EO) data processing, and (4) meteorological/hydrological data processing and analysis CV including a list of scientific outputs (thesis
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design in the quantitative social sciences (e.g. through coursework). Advanced skills in R, including data wrangling, visualisation, and analysis, as evidenced in prior work (e.g. Master’s thesis
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genomics or bioinformatics ecological data analysis Experience with all of these techniques is not expected. Curiosity, independence and enthusiasm for interdisciplinary science are more important than
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, Bioinformatics, or a closely related discipline. Relevant experience in Molecular Microbiology, Microbial Genomics/Metagenomics, Culture-based Microbiology, Bioinformatics or Quantitative Data Analysis is an
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collection, data analysis, writing scientific articles, and knowledge dissemination. Be able to translate methodological specifics to non-computational researchers Contribute both academically and socially