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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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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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that define protein structures, functions, dynamics and interactions Protein structure prediction and modelling, e.g. in Rosetta, MODELLER, AlphaFold, etc. Protein-peptide complex prediction or docking
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Understanding of the principles that define protein structures, functions, dynamics and interactions o Protein structure prediction and modelling, e.g. in Rosetta, MODELLER, AlphaFold, etc. o Protein
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and machine learning to establish a modeling framework that uses omic data for providing effective degradation rates of biomolecules and predictions of their impact on soil organic matter turnover
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. However, predicting effects of increasing aridity on soil OC stocks is not yet possible because above- and belowground processes of litter decomposition and soil organic matter (SOM) stabilization
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predicts the interactions of the evidentials with different types of speech act and syntactic contexts. The position begins on October 1, 2025 (or shortly after) and will run until June 30, 2029. The ideal
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
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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