Beyond-5G and 6G communication will focus on cloud-native and artificial intelligence (AI) centric design of communication networks to obtain ubiquitous connectivity, near-zero latency  and an extremely high reliability. The goal is to enable ambitious and challenging use-cases and applications relating to the augmented/virtual reality, holographic communications, digital-twins, metaverses and industry 5.0, to name a few. In terms of Radio access network (RAN) design,  OPEN-RAN defined by the O-RAN alliance has emerged as a potential RAN candidate. OPEN-RAN architecture promises interface interoperability between different RAN components, embraces AI/ML extensively in the RAN design, and follows the cloud-native principles to allow an increased RAN disaggregation.

The PhD candidate will work on the broadly-defined topic of interactions of AI/ML techniques and 6G RAN architecture. There are many directions possible such as optimization of AI/ML training/execution in RAN, extending the AI/ML in Open-RAN to sub-frame levels decision making, privacy-preserving AI/ML induction in a highly disaggregated RAN architecture such as Open-RAN,  and end-to-end resource allocation (network slicing) design, etc.  Based on the interest of the PhD candidate, a specific research direction will be chosen.

As part of the Advanced Networking Lab and the Center for Wireless Technology (CWTe), the project invites 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 with the leading national/international researchers working at the intersection of AI/ML and future telecommunication networks.

Minimum qualifications

1. A MSc degree in Electrical Engineering, Computer science or Telecommunications engineering.
2. A good understanding of 5G Radio Access Networks concepts such as Disaggregation,  Network Slicing and NFV.
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-RAN concept and knowledge of the open source platforms for 5G RAN implementation, e.g.,  OpenAIRInterface.
2. Experience with Machine  learning libraries(PyTorch, Keras) and toolkits.

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.
• 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.