6G mobile networks will most probably emerge as a wide envelop of wired and wireless technologies to satisfy even the most demanding applications. Yet, their dependence to distributed AI at the edge poses significant challenges at design-time and runtime. On the one hand, edge computing pushes our computing paradigm to lower energy efficiency and intensity as it cannot harvest on the benefits of computing instances concentration (i.e. optimized cooling and management overhead) at ultra-large data centers. On the other hand, the promise of edge computing is to enable ultra reliable and low latency applications that the current paradigm does not facilitate. A main barrier for power efficient ultra reliable and ultra low latency edge computing is the disjoint optimization of the network connecting the computing instances and the schedule of tasks to those instances. For instance, while Kubernetes allocates tasks to computing instances, SDN controllers separately optimize their network paths that interconnect them.

The main objective of this PhD position is to explore novel methods/techniques from distributed AI domain able to capture the requirements of interconnected tasks, the short/long-term availability of computing instances, the short/long-term capacity of network links and design at runtime ultra reliable and low latency network and compute slices.

As part of the Advanced Networking Lab and the Center for Wireless Technology (CWTe), the project invites candidates with strong analytical skills and will to apply and experiment with novel approaches on our computing cluster, 5G Core, Backhaul and/or Radio Access Network laboratory testbeds. The position is embedded to a large European wide consortium HiCONNECTs of 45 partners (Nvidia, Thermo Fisher Scientific, NXP Semiconductors, to name but a few).

The PhD researcher should demonstrate:

• Self-drive, proactivity, curiosity and execution power.
• Creativity and critical thinking and an ability to cooperate with internal and external partners.
• Master of Science degree in Computer Science or Electrical Engineering with excellent grades in related courses (e.g. distributed systems, networks, telecommunications, operating systems, AI/ML).
• Deep understanding in wired/wireless communications and network implementations.
• Strong theoretical and practical knowledge and experience with artificial intelligence techniques, esp. recurrent neural networks and reinforcement learning.
• Interest in combining theory and experiments and well-developed analytic skills.
• Excellent communication skills.
• Excellent proficiency (written and verbal) in English.

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.