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Research Associates (Postdocs) in Machine Learning for 5G Cognitive Radio Networks

University of Luxembourg

Luxembourg, Luxembourg
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Full Time
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University of Luxembourg
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Job Details

The University of Luxembourg is a multilingual, international research University.

The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from PhD holders in the general area of wireless communications. SnT is carrying out interdisciplinary research in secure, reliable and trustworthy ICT systems and services, often in collaboration with industrial, governmental or international partners. Recently, Prof. Bjorn Ottersten Director of SnT, has been awarded the prestigious European Research Council (ERC) Advanced Grant to pursue research on cognitive radio networks supported by machine learning algorithms. For further information you may check: and .

The University of Luxembourg is looking for its Interdisciplinary Centre of Security and Trust (SNT) for a :

Research Associates (Postdocs) in Machine Learning for 5G Cognitive Radio Networks

  • Ref: R-STR-5010-00-B
  • Fixed Term Contract 2 years (CDD), full-time 40 hrs/week
  • Number of positions:  At least 1

 The Centre is rapidly expanding its research activities and is seeking highly motivated Research Associates (PostDocs) who wish to contribute to its partnership and ERC research projects. The main research area is on Cognitive Radio Networks which incorporate ideas from Machine Learning and require a combination of mathematical tools from Statistics, Optimization and  Control Theory.  Machine learning methods will be used for actively learning a set of features describing the wireless environment and subsequently for making distributed or centralized decisions on the cross-layer resource allocation using the paradigms of Software-Defined Radio and Networking. The desired performance indicators include the throughput of the cognitive network, the cumulative interference towards primary systems and the convergence rate of the developed algorithms. 

For further information, please contact

Your Role

The successful candidates will join a strong and motivated research team lead by Prof. Björn Ottersten and Dr. Symeon Chatzinotas.

The position holders will be required to perform the following tasks:

  • Shaping research directions and producing results
  • Attracting funding in cooperation with industrial partners
  • Coordinating research projects and delivering outputs
  • Providing guidance to PhD and MSc students
  • Disseminating results through scientific publications
  • Assisting in teaching duties
  • Organizing relevant workshops


Your Profile

The candidates should possess a PhD degree or equivalent in Electrical/Electronics Engineering, Computer Science or Applied Mathematics.

The ideal candidate should have both project-based experience (FP7/H2020, ESA, Industry) and a publication record in a number of the following topics:

  • Applications of machine learning in communication systems
  • Cross-layer Resource Management & Optimization
  • Software Defined Radio and Networking

 and be familiar with a number of the following mathematical tools:

  •  Non-parametric statistics
  • MCMC sampling methods
  • Bayesian Reasoning for Classification, Clustering, Regression and Ranking
  • Convex Optimization
  • Stochastic, Robust or Chance-Constrained Optimization
  • Dynamic Programming
  • Compressed Sensing

Development skills in MATLAB or C++ are required.  Exposure to the latest standards in terrestrial and satellite communications as well as theory and methods of optimization are desirable. Hands-on experience is Software Defined Radio/Networking is also desirable. 

Fluent written and verbal communication skills in English are required.

We offer

The University offers a two-year employment contract and may be extended up to five years. The University offers highly competitive salaries and is an equal opportunity employer. You will work in an exciting international environment and will have the opportunity to participate in the development of a dynamic and growing centre.


Application should be submitted ONLINE and include:

  • Full CV, including list of publications and name (and email address, etc) of three referees
  • Transcript of all modules and results from university-level courses taken
  • Research statement and topics of particular interest to the candidate (300 words).

Please apply online until 1st August, 2017. 

Early submission is encouraged; applications will be processed upon arrival.



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