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signal processing AI/ML for communication systems Self-supervised ML, meta learning PHY/MAC optimization of wireless communication systems Robust, reliable, or explainable ML Experience with large-scale
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: Strong background in communication theory, signal processing, and wireless communications Proven track record of publications in relevant IEEE journals and conferences Extensive experience in physical
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or
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Autonomous Transportation. As far as technical enablers are concerned, we leverage expertise on advanced technologies including semantic/task-oriented data processing, signal processing, network resource
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LevelPhD or equivalent Research FieldEngineering » Communication engineeringEducation LevelPhD or equivalent Skills/Qualifications Official Doctoral Degree in Physics or Telecommunications Engineering
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: Strong background in communication theory, signal processing, and wireless communications Proven track record of publications in relevant IEEE journals and conferences Extensive experience in physical
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or
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processing, signal processing, network resource management to improve the performance of the future wireless communication systems. Finally, due to the large-scale nature, complexity, and heterogeneity of 6G
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, telecommunications or related field. Other requirements include Strong background in communication theory, signal processing, and wireless communications, Extensive experience in physical (PHY) layer algorithm design