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of self-assembly for specific types of molecules. Here, we use symmetry and the geometric properties of the molecules in order to calculate bounds that help to predict specific behavior. Moreover, we would
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micrometer resolution, allowing validation of the model predictions. • Validation and evaluation of the RFBs with optimized hierarchical electrodes
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. Here, we use symmetry and the geometric properties of the molecules in order to calculate bounds that help to predict specific behavior. Moreover, we would like to more widely explore the possibility
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fields, viz. AI driven materials property prediction and high thoughput materials development. Computational studies will be performed on Jülich`s world-class computational and AI infrastructure. Your
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heterogeneous and opportunistic sensor networks. Therefore, such an approach may significantly improve rainfall and runoff predictions. Research goals: Our primary goal is to improve the accuracy and prediction
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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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formation of two- and three-dimensional DNA structures which self-assemble from a number of interacting single-stranded DNA molecules. An accurate prediction of DNA structures still remains difficult, which
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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