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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 17 days ago
complexes. The successful candidate will develop novel graph neural network (GNN) architectures to learn dynamic information from molecular dynamics (MD) simulations of protein-protein and protein-nucleic
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working on interdisciplinary research problems at the intersection of mathematics, theoretical computer science and quantum information theory? Are you interested in algebraic complexity theory, fast matrix
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About the Opportunity SUMMARY The Network Science Institute (NetSI) is hiring one Postdoctoral Research Associate to join the newly formed Complexity & Society Lab (the “&-Lab”). The &-Lab is an
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: Developing physics-informed neural networks (PINNs) for complex dynamical systems modeling and observer design Creating and validating digital twin architectures that incorporate physical laws and constraints
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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complexity theory, fast matrix multiplication algorithms, the geometry and representation theory of tensors, asymptotic spectrum duality, and applications? The research group of Jeroen Zuiddam at University
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
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develop transformative therapies for glioblastoma (GBM) by understanding the disease on its own biological terms, within the complex context of the human central nervous system. We are entering an exciting
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management to improve the performance of the future wireless communication systems. Finally, due to the large-scale nature, complexity, and heterogeneity of 6G networks, for their analysis and optimization, we
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, data-limited, and dynamically evolving environments. Applications include complex engineered systems such as intelligent communication networks, distributed computing platforms, and quantum-enhanced