52 data-visualization-analysis Postdoctoral positions at Aarhus University in Denmark
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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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others. Essential: Strong data analysis and machine learning skills and experience with PyTorch (or equivalent frameworks). Hands-on experience with data representation and embeddings, ideally applied
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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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, including quantitative PTM analysis, mass spectrometry method development, data-independent acquisition (DIA) strategies, laboratory automation, and scalable proteomics workflows. Both positions are initially
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with multi-colour flow cytometers. Project experience in virology preferentially knowledge of working in biosafety class 2/3 virus production and virus infected cell culture Single-cell analysis
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, and a waitlist control condition. Data will be collected by the time the postdoctoral researcher starts, allowing the researcher to focus on analysis, writing, and publication. The position is suited
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this position, we seek to strengthen the platform by embedding/developing additional tools for data processing and analysis. The starting point for the developments will be our EasyNMR platform (see
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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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carcasses for analysis. Your task will be to explore what we can learn from the beached bird data. Topics include the distribution of mortality in time and space, and among species; causes of death, as