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model systems zebrafish and fruit fly, and structural biology (including AlphaFold predictions and cryo-EM), we will dissect the roles of these novel mRNA export regulators and define how they interface
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micrometer resolution, allowing validation of the model predictions. Validation and evaluation of the RFBs with optimized hierarchical electrodes. What you bring to the table Very good master´s degree in
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tunnel testing and statistical modelling using extreme value theory, the project will yield predictive frameworks for structural risk under rare yet damaging wind conditions. The results will support
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! RESPONSIBILITIES: You will elucidate the molecular mechanisms driving the development of distinct malignant lymphoma subtypes and contribute to the identification of predictive biomarkers and novel therapeutic
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Jülich who are leaders in their respective fields, viz. AI-driven materials property prediction and high-throughput materials development. Computational studies will be performed on Jülich’s world-class
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of the Earth system at different temporal and spatial scales to improve predictive capability. Comprehensive education: Enjoy numerous opportunities for scientific training, skills development and problem
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separately, yet a reliable, open-source tool integrating a shallow-water solver and a multiphase porous-media solver within the same framework is missing. Without this coupling, it is not possible to predict
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computing to develop a continuous and local alternative to existing gradient-based learning rules, bridging theories of predictive coding with event-based control/ Simulate models of the learning algorithm
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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