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these determinants, we will harness the diversity of aspartic proteases from the model plant Arabidopsis thaliana and deploy chemical synthesis, advanced modelling, protease biochemistry, mass spectrometry and
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-specific inflammation” and aims to develop and apply advanced imaging tools to study immune cell dynamics in murine models of inflammation and cancer. More about our work: https://www.medizin.uni-muenster.de
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for analysis of the data you create. Your findings will be a vital part of understanding the evolution of cancer drug resistance in cell models and in patients. About you: You’re excited about our research
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the perspective of energy infrastructure. Using the existing energy system models of ICE-2, you will develop scenarios to analyze the effects on the German energy system and its robust design in a European context
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Leibniz-Institute for Plant Genetics and Crop Plant Research | Neu Seeland, Brandenburg | Germany | 7 days ago
have hands-on experience in crop genomics and managing genotyping data. You bring first experience with biostatistics methods, e.g. with mixed-models. You are familiar with data analysis using
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Neuroscience uses theoretical approaches from this broad range of disciplines to integrate experiment, data analysis and modelling in order to understand the brain. Furthermore, it makes a scientific language
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researcher positions for projects related to photo-electro-mechanical energy harvesting systems, including material synthesis, characterization, device integration, and material simulation. The IGK2495
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resource efficiency. A physics-based model for monitoring the condition of helicopter components is being developed as part of this project. With the help of flight test data, this model is to be calibrated
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with microstructural features and failure mechanisms Development of models to describe degradation mechanisms and predict component lifetime Presentation of research findings at project meetings
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available on site for the development of suitable radiotracers. One focus of the work is on the use and evaluation of large tomographic data sets to derive parameter data for reactive transport modeling