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microbial ecology can be used to inform sustainable management practices that increase soil carbon stocks and reduce nitrogen losses. And the main focus of your position will be soil molecular analysis and
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vesicle-based signalling to nutrient-use efficiency. Manage data, perform statistical analysis and exchange results with project partners producing synthetic EVs and modelling the data. Contribute
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methods for approaches such as model-data fusion techniques. The main focus of your position will be to develop and apply a scalable process-based modeling framework to evaluate climate-smart management
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. Experience with one or more of the following will be considered an advantage: RNA sequencing or other omics technologies, including data analysis; advanced microscopy or image analysis; renal physiology
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Associate Professor Martin Thomsen’s group on data analysis and model development. You will report to the Professor Ian Mills/Associate Professor Emma Evergren. Your competences You have academic
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vegetation ecology, plant community ecology or multi-taxon biodiversity analyses analysis of field, camera-trap, trait, citizen-science, spatial or remote-sensing data GIS, spatial modelling, remote sensing
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radiotherapy. Experience with photon-counting CT will be a considerable advantage. Deep learning knowledge will be an asset. CT image analysis skills is a prerequisite. You should have a strong theoretical
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) to study atomic structures of optically excited small unit cell crystals. The project involves measurements, data reduction and structure refinement of large serial femtosecond X-ray (SFX) crystallography
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related departments. Contact information For further information, please contact: Professor Troels Skrydstrup, +45 28 99 21 32, [email protected]. Application procedure Shortlisting is used. This means
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employment is Aarhus University with affiliated institutions. Contact information For further information, please contact Professor Kim Daasbjerg at +45 23485249 or [email protected]. Application deadline