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sciences a pleasant and respectful working atmosphere integration into a successful and committed team in an international environment and network flexible and family-friendly working time models and the
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contributes to the improvement of climate prediction models. The Atmospheric Chemistry and Atmospheric Microphysics departments are looking for a committed doctoral student to carry out this project. You can
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such as the NEPS. Potential research areas include (but are not limited to): Item response modeling of achievement tests Analysis of process data (e.g., response times) to enhance competence measurements
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the diversity of aspartic proteases from the model plant Arabidopsis thaliana and deploy chemical synthesis, advanced modelling, protease biochemistry, mass spectrometry and structural analysis methods. A
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sound background in geophysical fluid dynamics, experience in numerical ocean or atmospheric modelling, and experience with numerical data analysis. Good scientific presentation, writing, and
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analysis problems, especially tracking the motion of objects, which are driven by real applications in life science research Developing solutions to integrate large foundation models into microscopy image
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experience growing, managing, and phenotyping plants in the field and greenhouse. You have experience using modern approaches in root phenotyping, image analysis, or simulation modeling to understand
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of Munich, Cologne and Hanover as well as the German Weather Service in Offenbach and Lindenberg. The partners combine leading expertise in modeling and observing clouds and their radiative properties with
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combines microbial genomics, transcriptomics, and in vitro infection models to explore the adaptive trade-offs between drug resistance and virulence phenotypes. The position is funded for 3 years and
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools