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experience in pig nutrition. Experience in conducting different types of animal experiments. Skills in the analysis of experimental data and the scientific communication of research results. For non
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one language used for computational modelling and data analysis, such as Python, R, Julia, MATLAB, NetLogo, or C++. Preferably, you have demonstrated experience with data-driven computational modelling
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monitoring, control and predictive analysis during experimental operation. Both positions include reporting and publication of the results, and the opportunity to contribute to the supervision of PhD and MSc
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Professor Jesper W. Schneider. The position will involve a combination of quantitative and qualitative research tasks, including bibliometric analysis, social network analysis, survey design and analysis
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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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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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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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, 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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, 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