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of lignocellulose and how it is degraded in Nature Knowledge of microbial denitrification and analysis of relevant gases Experience with bioinformatic analysis including comparing/aligning 3D-structures (PyMOL
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, proteomics, gut microbiome analyses, and/or other nutrigenomic tools). Process and perform statistical and bioinformatic analysis of data. To generate scientific communication and publications. The successful
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). Process and perform statistical and bioinformatic analysis of data. To generate scientific communication and publications. The successful candidate is expected to have a PhD education plan approved by
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datasets and using R and other relevant bioinformatics tools. Experience with lab work particularly molecular methods such as RNA and protein extraction or cloning. Experience with plant transformation using
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experiences and skills will be emphasized: Experience with handling large datasets and using R, GIS and bioinformatics tools. Experience with modelling methods, including analysis of ecological gradient
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hybridization, confocal microscopy, 3D imaging, in vitro fertilization). Use of bioinformatics tools to increase mechanistic insights. Research visits abroad might be possible. The successful candidate is
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bioinformatics Personal characteristics important for the positions are: Strong scientific capacity and analytical skills Good social and collaboration skills Ability to work independently Driver’s license