PhD Researcher on Video Streaming services for Immersive applications

Gent - PhD
More than two weeks ago

We are currently looking for a PhD researcher to support our research track on Management of Video Streaming services, more specifically in the domain of immersive (virtual and augmented reality) applications.

About IDLab

IDLab ( performs fundamental and applied research on internet technologies and data science. Major research areas are machine learning and data mining, semantic intelligence, distributed intelligence for IoT, cloud and big data infrastructures, multimedia processing, wireless and fixed networking, electromagnetics, RF and high-speed circuits and systems. IDLab has a unique research infrastructure used in numerous national and international collaborations. IDLab collaborates with many universities and research centers worldwide and jointly develops advanced technologies with industry (R&D centers from international companies, Flanders’ top innovating large companies and SMEs, as well as numerous high-tech start-ups).

IDLab is a core research group of imec and a large part of IDLab's research activities are embedded in Ghent University. The research on wireless networking is a joint activity between the University of Antwerp and Ghent University. IDLab is the integration of the former research groups DSLab, IBCN and MOSAIC and counts about 300 members (40 professors, 50 post docs, 200 researchers, 15 support staff members).

What you will do

Research area

We are currently looking for a PhD researcher to support our research track on Management of Video Streaming services, more specifically in the domain of immersive (virtual and augmented reality) applications.

Video streaming applications will continue to dominate Internet traffic, driven by the rising popularity of over-the-top adaptive streaming solutions. To keep up with the ever more stringent quality and latency requirements in virtual, augmented and immersive environments, novel architectures and protocols have to be researched, as well as machine learning techniques to autonomously deal with highly variable network characteristics, predict user behaviour and optimize Quality of Experience (QoE) dynamically.

Topics that will therefore be addressed in this research track include (but are not limited to) the following:

  • machine learning algorithms for user profiling, traffic characterization and behaviour prediction;
  • network and application data analysis in support of QoE optimization,
  • novel (5G) network architectures and protocols to support video streaming services;
  • storage, computing and network resource optimization;
  • user-centric requirement analysis for immersive and high-quality video applications.


  • You will conduct research on future video streaming solutions in the framework of national and European research projects.
  • You will build up hands-on experience by implementing novel technologies and machine learning algorithms and by evaluating these through simulations and emulations on imec’s technical lab.
  • You will publish and present results both at international conferences and in scientific journals.

What we do for you

We offer a very challenging, full-time position in an inspiring, flexible and very dynamic environment. You will join a young and enthusiastic team of developers, researchers, post-docs and professors. You will receive a competitive salary. The position is available immediately.

Who you are

  • You have a master degree in computer science, informatics or electrical engineering.
  • You have a keen interest in network management technologies, preferably in the domain of video streaming services.
  • You have analytical skills, you are well-organized and able to autonomously plan and execute tasks.
  • You are a team player and have excellent communication skills in English.
  • You are highly proficient in a variety of programming languages (e.g. Java, Python, C/C++).
  • You have a proven track record in scientific publishing.

Share this on

This website uses cookies for analytics purposes only without any commercial intent. Find out more here.

Accept cookies