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Field
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(7T fMRI, MR Spectroscopy), electrophysiology (EEG), interventional (TMS, tDCS) and neurocomputational (machine learning, reinforcement learning) approaches to understand the network dynamics
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de Rham" methods, the main feature of which is to reproduce subtle mathematical properties expressed by Hilbert complexes at the discrete level. The developments envisaged within the NEMESIS project
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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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forcing of structural vibrations, often linked to the presence of complex flow features such as wakes and flow separation and their interaction, whose numerical representation can be challenging for legacy
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is the nexus of a broad collaboration network. Each year, CFN staff members support the research of nearly 600 external facility users. Three strategic nanoscience themes underlie the CFN scientific
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speech (i.e., statistical learning), we aim to understand the neurophysiological underpinnings of the beneficial effects of music exposure across early language acquisition. The underlying neural network
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Networks. Preferred Qualifications: ● Experience in quantum network experiments/devices. ● Experience in writing research proposals. ● Experience in supervising/guiding PhD and/or MS students
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in network science. NetSI faculty and researchers are working to advance the understanding of complex systems through the lens of networks, and to apply this knowledge to solve real-world problems in a
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Networks. Preferred Qualifications: ● Experience in quantum network experiments/devices. ● Experience in writing research proposals. ● Experience in supervising/guiding PhD and/or MS students
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to conduct world-leading fundamental and applied research within communication, networks, control systems, AI, sound, cyber security, and robotics. The department plays an active role in transferring