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Position: Research Associate (Postdoc) in machine learning optimization and FPGA acceleration for 5G/6G physical layer
Institution: University of Luxembourg
Location: Luxembourg City, Luxembourg
Duties: Optimize 5G New Radio (NR) with waveform based on orthogonal frequency-division multiplexing (OFDM) and its evolution for satellite communication (Satcom) applications; Design machine learning models to reduce the computational complexity and power consumption of several physical layer processing blocks of the receiver, such as decoding, channel estimation, and demodulation; Ensure the ML models reduce the complexity while maintaining satisfactory performance in terms of throughput and bit-error-rate
Requirements: A PhD degree in Telecommunication Engineering, or Electrical Engineering or Computer Science/engineering with a focus on wireless communications and AI/ML tools and methods; Experience in signal processing for wireless communications algorithms. Especially strong knowledge of the physical layer (tasks such as decoding, demodulation, and estimation); Background in optimization theory; Experience using machine learning to solve/improve physical layer processing tasks, especially decoding
   
Text: Research Associate (Postdoc) in machine learning optimization and FPGA acceleration for 5G/6G physical layer Optimize 5G New Radio (NR) with waveform based on orthogonal frequency-division multiplexing (OFDM) and its evolution for satellite communication (Satcom) applications; Design machine learning models to reduce the computational complexity and power consumption of several physical layer processing blocks of the receiver, such as decoding, channel estimation, and demodulation; Ensure the ML models reduce the complexity while maintaining satisfactory performance in terms of throughput and bit-error-rate A PhD degree in Telecommunication Engineering, or Electrical Engineering or Computer Science/engineering with a focus on wireless communications and AI/ML tools and methods; Experience in signal processing for wireless communications algorithms. Especially strong knowledge of the physical layer (tasks such as decoding, demodulation, and estimation); Background in optimization theory; Experience using machine learning to solve/improve physical layer processing tasks, especially decoding
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