Research Associate in Graph Signal Processing for Large-Scale Networks (*gn)
Université du Luxembourg
Alphonse Weicker, Luxembourg
il y a 6j

Your Role

The successful candidate is expected to perform the following tasks :

  • Contributing to expand group’s fundamental research on Graph Signal Processing (GSP)
  • Investigating novel learning-assisted GSP algorithms for Beyond 5G wireless networks
  • Coordinating research projects and preparing project deliverables
  • Disseminating results through scientific publications and conferences
  • Preparing new research proposals to attract industrial, national and European projects
  • Providing assistance in the supervision of PhD students
  • For further information, please contact : Dr. Shree Krishna Sharma (shree.sharma

    Your Profile

  • A PhD degree in signal processing, machine / deep learning or a closely related field in Electrical Engineering, Computer Science or Applied Mathematics
  • Strong knowledge on some of the following topics : graph signal processing, 5G and beyond wireless networks, large-scale dynamical systems, network topology inference, dictionary learning, machine / deep learning techniques and tools (TensorFlow, PyTorch or GreyCat), random matrix theory and optimization methods
  • Sound publication track-record on one or some of the following areas : signal processing on graphs, GSP for wireless networks, learning models over dynamic graphs, machine / deep learning for wireless communications, learning-assisted optimization and data analysis with GSP
  • Strong programming skills in MATLAB and Python, R or C++
  • Highly committed, excellent team-worker, and strong critical thinking skills
  • Excellent written and oral communication skills in English
  • We offer

    The University offers an initial two-year employment contract, which may be extended up to five years. The University offers highly competitive salaries and is an equal opportunity employer.

    Further Information

    Applications, written in English should be submitted online and include :

  • Curriculum Vitae (including your contact address, work experience, publications)
  • Cover letter indicating the research area of interest and your motivation
  • A research statement (max. 1 page)
  • Contact information for 3 referees
  • All qualified individuals are encouraged to apply.

  • gn gender neutral.
  • Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system.

    Applications by email will not be considered.

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