PhD Fellowship in Machine Learning 2017, Luxemburg

Publish Date: May 17, 2017

Fellowship Description

The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from PhD candidates in the general area of wireless communications and networking. 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.

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

PhD Positions in Machine Learning for 5G Cognitive Radio Networks

  • Ref: R-STR-5010-00-B
  • Fixed Term Contract up to 3 years in total, pending satisfaction of progress milestones (CDD), on full time basis (40hrs/week).
  • Number of positions: at least 1

The Centre is rapidly expanding its research activities and is seeking highly motivated PhD candidates 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. 


The successful candidates will join a strong and motivated research team lead by Prof. Björn Ottersten and Dr. Symeon Chatzinotas in order to pursue a PhD on the following topics:

  • Machine Learning for 5G Cognitive Radio Networks

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

  • Carrying out research in the predefined areas
  • Disseminating results through scientific publications and conference presentations
  • Participating in proposal drafting
  • Assisting in organization of relevant workshops

Qualification: The candidates should possess an MSc degree or equivalent in Electronic Engineering, Computer Science or Applied Mathematics.

Your Profile

The ideal candidate should have some knowledge and experience in a number of the following topics:

  • Cross layer aspects of digital communication systems
  • Applications of machine learning in physical/network layer of digital communications
  • Terrestrial/Satellite Communication Standards

and be familiar with the principles of

  • Linear algebra
  • Probability theory
  • Optimization theory
  • Multivariate calculus and statistics
  • Machine learning

Development skills in MATLAB or C++ are required.

Language Skills: Fluent written and verbal communication skills in English are required.

We offer

The University offers a Ph.D. study program with a Fixed Term Contract up to 3 years in total, pending satisfaction of progress milestones (CDD), on full time basis (40hrs/week). The University offers highly competitive salaries and ample opportunities for training activities towards professional development. You will work in an exciting international environment and will have the opportunity to participate in the development of a dynamic and growing centre. University of Luxembourg is an equal opportunity employer.


How to Apply

Application should include:

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

All qualified individuals are encouraged to apply ONLINE.

For more information please click "Further Official Information" below.

Further Official Information

Link to Original

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