PhD on AI/ML-assisted zero touch management of 6G networks

PhD on AI/ML-assisted zero touch management of 6G networks

Published Deadline Location
22 Feb 18 Aug Eindhoven

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Job description

The increasing cloudification of mobile networks is leading to increased complexity of network management due to the use of heterogeneous hardware and software network elements. The extreme high performance(latency, reliability, data rates, etc.) requirements of beyond-5G/6G applications necessitate the real-time diagnostic of network malfunctions and possible (automated) maintenance for prompt recovery. To enable this, advanced network monitoring solutions that take input from both the data plane and control plane to ensure a sustained network operation are highly desired. In particular, network management solutions that can minimize the human intervention in complex network management tasks (zero touch management), are of particular interest due to the rapidly growing complexity of end-to-end mobile networks and the increasing proliferation of machine-to-machine (M2M) communication.

Within the European  MSCA-DTN project SCION, which aims to employ the key technologies of Digital Twin, blockchain and AI/ML for dependable network connectivity, we are looking for a highly motivated PhD candidate to explore novel techniques of network management. In particular, the objective is to come up with automated (zero touch) network management mechanisms utilizing AI/ML techniques to handle the unexpected situations. As part of the Advanced Networking Lab and the Center for Wireless Technology (CWTe), we solicitate applications from candidates with strong analytical skills and willingness to test novel approaches on our 5G Core, Backhaul and Radio Access Network laboratory testbeds. There will be ample opportunities to collaborate within the MSCA-DTN SCION consortium representing researchers from the leading European Universities and industrial research organizations working at the forefront of 6G mobile networks.


Eindhoven University of Technology (TU/e)


Minimum qualifications
  1. A MSc degree in Electrical Engineering, Computer Science or Telecommunications engineering.
  2. A good understanding of 5G/6G Radio Access Networks concepts such as machine to machine (M2M) communications,  disaggregation,  network slicing and network function virtualization.
  3. Knowledge of machine learning and mathematical optimization  techniques
  4. Programming experience in Python and/or C++
  5. A team player who is willing to work in a multi-cultural and international environment.
  6. A good level of English knowledge skills.
Preferred qualifications:
  1. Familiar with open source platforms for 5G RAN  and Core implementation, orchestration platforms, etc.
  2. Experience with machine  learning libraries(PyTorch, Keras) and toolkits
  3. Interest in cloud computing and approaches such as containerization, DevOps, CI/CD, etc.

Conditions of employment

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:
  • Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
  • Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,770 max. €3,539).
  • A year-end bonus of 8.3% and annual vacation pay of 8%.
  • High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
  • An excellent technical infrastructure, on-campus children's day care and sports facilities.
  • An allowance for commuting, working from home and internet costs.
  • A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.


  • PhD
  • Engineering
  • max. 38 hours per week
  • University graduate
  • V36.6384


Eindhoven University of Technology (TU/e)

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De Rondom 70, 5612 AP, Eindhoven

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