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? No Offer Description NEWTON is a training network that a revolutionary approach of a converged wireless-optical network architecture that makes reality an efficient 6G Cell Free (CF)-based access
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programming and hands-on experience with AI frameworks (PyTorch, TensorFlow, etc.). Domain Knowledge: Solid understanding of telecommunication networks and architectures. Language: Fluency in English (written
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architectures (including gap-waveguide technology) to maximize isolation, efficiency, and compactness. The successful candidate will engage in antenna design, electromagnetic modeling, array integration, and
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Science, Cybersecurity, or related field, with a solid academic record Strong foundation in Network Security, Privacy Enhancing Technologies (PETs), or Applied Cryptography Basic knowledge of B5G/6G architectures (O-RAN
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Materials Group (NANOUP) is focused on controlling the supramolecular assembly of molecules, biomolecules and nanoscale building blocks at the nanometer scale for the design of novel functional architectures
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at proposing a revolutionary approach of a converged wireless-optical network architecture that makes reality an efficient 6G Cell-Free (CF)-based access network for high-density and high coverage deployments
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This position targets to develop a novel native integration of AI/ML in the new 6G RAN architecture that adds an extra level of coordination and conflict resolution between the different AI/ML models operating