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atomistic simulation methods, such as molecular dynamics, density functional theory, and machine-learning force fields, to elucidate the deformation mechanisms activated by external stimuli. The candidate
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| Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 31.03.2032 Reference no.: 5115 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique
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Mattelaer, Christophe Ringeval). Research activities in include SM and BSM aspects of collider physics (LHC and future colliders, simulation tools, machine learning, effective field theories, amplitude
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 18 days ago
lives. The Theis Lab at the Computational Health Center is internationally recognized for pioneering methods in machine learning, single-cell analysis, and computational modeling of complex biological
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machine learning technologies in order to provide evidence-based decision support tools in near real time across a variety of thematic domains: disaster risk reduction, sustainable agri-food systems
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goals and those of faculty mentor; and publication of research findings/scholarship during postdoc appointment period. Projects in the Rocha lab address the evolutionary history of populations and species
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genome-resolved multi-Omics methods, statistical/metabolic modeling, and machine learning. The postdoc will apply these approaches to generate a systems-level understanding of microbiomes including
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, including Machine Learning Interatomic Potentials. • Other research experience will be considered. Personal Competences: • Strong commitment • Attention to detail • Demonstrated ability to work with deadlines
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silico identification of candidate developmental pathways explaining tradeoff variation. Contribute to advanced statistical analyses and interpretable machine learning approaches (in collaboration with
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are looking for a motivated postdoc with solid experience in bioinformatics and in machine learning. The position centers on SRPs and LLPS, and the successful candidate will contribute to several ongoing