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physics and condensed matter theories to address the problem of fracture in complex materials. You will be working with experimental model systems and numerical simulations of materials that exhibit
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, Heidelberg and Mannheim, our scientists collaborate across disciplines to unravel the complexities of disease at the systems level – from molecules and cells to organs and entire organisms. Through strong
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tomorrow’s medicine through our discoveries of today. At locations in Berlin-Buch, Berlin-Mitte, Heidelberg and Mannheim, our scientists collaborate across disciplines to unravel the complexities of disease
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learning projects. The Scientific Program Manager will work in a complex, multi-team effort to steer and coordinate development of next-generation machine learning models for biomolecular structure
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Molecular Physiology and Functional Biochemistry. We are looking for a researcher investigating biochemical and molecular processes that underlie physiological functions in complex biological systems
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seeking enthusiastic, full-time post-doctoral Flatiron Research Fellows to work on information processing in biological networks and nonequilibrium thermodynamics of living systems. Current areas
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PhD fellowship at the Copenhagen Center for Glycocalyx Research at the Department of Cellular and Mo
(CGR) The Copenhagen Center for Glycocalyx Research (CGR) aims to uncover the vital role of the glycocalyx, a cell surface layer of complex glycans, that integrates signals from cells and their
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complex challenges in economics and business. In addition, the DataScience@Uni Vienna research network offers extensive opportunities for cooperation with researchers from various departments and faculties
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of modeling higher-order relational structures such as hypergraphs and simplicial complexes, which are prevalent in complex biological systems like protein assemblies, signaling pathways, and metabolic networks
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increasingly complex networks. By deploying and advancing techniques such as machine learning, graph-based network analysis, and synthetic data generation, the project tackles key challenges in anomaly detection