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rules for Marie Skłodowska-Curie grant holders, will consist of a gross annual salary 38 k€ EUR salary (gross amount for the employee before tax). Of this amount, the estimated net salary* to be perceived
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highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud
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to ensure that mesh elements are aligned with the magnetic field lines in order to reduce errors in regions with strong anisotropy, improve numerical stability, and accurately reproduce the underlying physics
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networks that govern the dynamics of dissipative supramolecular assemblies. Main responsibilities of the candidate will include: Develop theoretical frameworks and quantitative models describing non
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learning methods. Develop deep learning architectures (e.g., variational autoencoders, graph neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view
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the Job related to staff position within a Research Infrastructure? No Offer Description Description The Division of Engineering and the Center for Interacting Urban Networks (CITIES) at New York
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 6 days ago
qualified Post-Docs interested in Computational Social Science. This application call is targeted to the broad topic of artificial intelligence, computing, and society. Research Themes and Teams The Network
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methods with optimization and decision-support models. Background in one or more of the following: time-series analysis, neural networks, forecasting, uncertainty quantification, sensitivity analysis
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. Indeed, the methods currently used rely on optical image databases of various avalanche observations. A deep neural network was trained on this data to enable automatic avalanche detection FIGURE 1 (a) [1