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Position: Research Associate in 6G Radio Access Network Design and Optimization
Institution: University of Luxembourg
Location: Luxembourg City, Luxembourg
Duties: Integrate with the SIGCOM research group and contribute to the SIGCOM on-going research projects; Identify and shortlist potential technological solutions to improve the performance of future 6G RAN; Design and develop algorithms able to provide a good performance-complexity trade-off for the identified scenarios and use cases; Compare conventional optimization tools with advance artificial intelligence solutions; Implement a SW-based demonstrator for testing the developed algorithms; Compare with state-of-the-art and conventional solutions via numerical simulations; Disseminating results through scientific publications and conferences; Preparing new research proposals to attract new projects; Providing assistance in the supervision of PhD students
Requirements: A PhD degree in Telecommunication Engineering, or Electrical Engineering or Computer Science/engineering with a focus on artificial intelligence; Experience with 5G communication systems; Experience with non-terrestrial networks (NTNs) is considered a plus but it is not required; Solid background on mathematical optimization tools; Good knowledge of the recent trends in machine learning design; International experience is desirable; Sound publication track record in relevant international conferences and top journals (at least one IEEE Transaction publication is mandatory); Strong programming skills in Python, MATLAB and LaTeX. Other languages such as Lava, Julia, C++, are desirable but not mandatory
   
Text: Research Associate in 6G Radio Access Network Design and Optimization Integrate with the SIGCOM research group and contribute to the SIGCOM on-going research projects; Identify and shortlist potential technological solutions to improve the performance of future 6G RAN; Design and develop algorithms able to provide a good performance-complexity trade-off for the identified scenarios and use cases; Compare conventional optimization tools with advance artificial intelligence solutions; Implement a SW-based demonstrator for testing the developed algorithms; Compare with state-of-the-art and conventional solutions via numerical simulations; Disseminating results through scientific publications and conferences; Preparing new research proposals to attract new projects; Providing assistance in the supervision of PhD students A PhD degree in Telecommunication Engineering, or Electrical Engineering or Computer Science/engineering with a focus on artificial intelligence; Experience with 5G communication systems; Experience with non-terrestrial networks (NTNs) is considered a plus but it is not required; Solid background on mathematical optimization tools; Good knowledge of the recent trends in machine learning design; International experience is desirable; Sound publication track record in relevant international conferences and top journals (at least one IEEE Transaction publication is mandatory); Strong programming skills in Python, MATLAB and LaTeX. Other languages such as Lava, Julia, C++, are desirable but not mandatory
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