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strong background in wireless and mobile networks, as well as machine learning, ideally with exposure to Reinforcement Learning (RL) or decision-making agents. You have an interest or background in network
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of virtualizing and forecasting the evolution of the radio-electric environment. In the second phase, the candidate will investigate machine learning and AI-driven algorithms for NTN channel prediction, enabling
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in AI (machine learning, neural networks, reinforcement learning, dynamic modelling and/or Bayesian inference). You have experience in software development with solid knowledge of one or more
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