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, the Max Planck Institute for Biogeochemistry houses a unique and flexible research program that grants German and foreign students a broad selection of learning opportunities while still maintaining a
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. You will employ the trypanosome model established in our group to study its swimming behavior in soft tissue-like surroundings. This project is a part of the DFG-SPP 2332 priority program “Physics
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, computational model development, data processing, and code implementation in close cooperation with scientists. The position is limited to 3 years. Equal opportunity is an important part of our personnel policy
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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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to understand, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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to the computational complexity of climate models, these will be replaced by physics-informed deep learning surrogates in the aforementioned model coupling. The project will initially focus on one main application
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scenarios and strategies for its successful implementation. Using existing ICE-2 energy system models, you will address questions such as: How do installation and retrofitting times impact the restructuring
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phenomena such as the spread of misinformation or the formation of filter bubbles. For this, we rely on rigorous probabilistic methods to model and analyse the intrinsic complexities of these systems
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to uncover new molecular strategies for safeguarding crops. Join a vibrant, interdisciplinary research environment where computational chemistry, biochemistry, molecular biology, and plant science converge
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interactions to uncover new molecular strategies for safeguarding crops. Join a vibrant, interdisciplinary research environment where computational chemistry, biochemistry, molecular biology, and plant science