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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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. 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
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for the Modeling of Biological and Sociotechnical Systems (MOBS Lab) within the Network Science Institute at Northeastern University. MOBS Lab focuses on research projects aimed at developing innovative mathematical
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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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collaborative research with Professors Alaïs Martin-Baillon, Jordan Norris, and Samreen Malik. The collaborative research will be on macroeconomic expectations, with a focus on firms and the role of networks
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | about 5 hours 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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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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and experimentation in the area of Multi-agent Agentic AI systems applied to 6G network and service management. By leveraging recent advances in Large Language Models (LLM) and other key agentic tools
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computational mesh generation. In this role, you will apply your software engineering skills to develop and validate computational results that support large-scale, physics-based simulations across a variety of
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 24 hours ago
to reconstruct open rose flowers in 3D. The key idea is to learn two neural networks that operate on different scales. The first network operates on the scale of the full flower to identify the flower architecture