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Framework (RDF). enables advanced data mining queries using the SPARQL query language. provides a natural language-based interface to perform these queries on the knowledge graph using a large language model
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research environment, comprising two full professors, one associate professor, one assistant professor, one postdoc, and a large number of PhD students. The project includes strong partnerships with
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of very large data sets, data analysis, and simulations of X-ray scattering and spectroscopy signatures of dynamic processes in battery materials. The theoretical/ simulation efforts are supported by
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large-scale whole genome and whole exome sequencing, RNA-seq, ATAC-seq, proteomics, and metabolomics data in a well-established cohort of childhood cancer survivors with clinically ascertained deep
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of science to applied technological research and partnership with industry. Your Tasks, Core Themes Candidates will have the opportunity to pursue one or more of the following core themes: 1. Large Pre-Trained
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causal networks that govern cellular behavior from large-scale single-cell datasets. Our group has pioneered computational approaches for: Inferring causal networks from Perturb-seq (interventional single
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processes. A demonstrated interest in data visualization and large-scale data analysis is highly desirable. The ideal candidate will have a keen interest in understanding complex biological systems
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tasks You will carry out research tasks in Prof. Wende's working group, particularly in the field of element-specific investigation of functional magnetic materials at large research facilities. In
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involves software development, measurements using local and large international facilities, and a keen eye on developing relations between local order and material properties. The candidate must have a
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from and strongly interact with the Helmholtz large-scale infrastructure project “SAFAtor”. Your responsibilities: Processing DAS data from different ongoing experiments in the study region Application