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at the interface of data science and the scientific domains pursued at the three participating Helmholtz centers. Methodologically, a broad range of topics is covered, from large-scale data management to data mining
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of topics is covered, from large-scale data management to data mining and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics
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, using techniques such as: High-dimensional data mining Tensor decomposition Causal inference Statistical process modeling Machine Learning Applications include public transport, private vehicles, traffic
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ontology alignment in physics and materials domains Build and maintain ontologies, OWL/RDF knowledge graphs, SPARQL endpoints, and open benchmarking suites to guarantee FAIR, reusable research data Mine and
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transcriptomics and single-cell RNA sequencing on patient samples • Mining and analyzing public cancer databases (TCGA, GEO, etc.) and omics data • Inferring TLS formation and maturation stages from
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/RDF knowledge graphs, SPARQL endpoints, and open benchmarking suites to guarantee FAIR, reusable research data Mine and link structure-property relationships from DFT, MD, phase-field, TEM/SEM, and
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Leibniz-Institute for Plant Genetics and Crop Plant Research | Neu Seeland, Brandenburg | Germany | 5 days ago
21 Aug 2025 Job Information Organisation/Company Leibniz-Institute for Plant Genetics and Crop Plant Research Research Field Agricultural sciences » Agronomics Agricultural sciences » Other
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datasets (e.g. scRNA-seq) to derive prior knowledge on AML dormancy Develop and apply integrative data analysis pipelines (e.g. MOFA, Scriabin, LIANA+, COSMOS) for mining and interpreting multi-omic datasets
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30.06.2025, Wissenschaftliches Personal The Chair of Software Engineering for Business Information Systems (sebis) at the Technical University of Munich is looking for outstanding candidates
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sensitivity and respect for diversity Desirable: Experience in cheminformatics, molecular modeling, or enzyme mechanisms Familiarity with databases, data mining, and knowledge management Why Join Us: Be part of