Research Associate (Postdoc) position in Robust Machine Learning for Multilayer 6G Communications Networks

The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from highly motivated PhD candidates in the general area of machine learning and radio resource allocation for emerging wireless networks within its Signal Processing and Communications (SIGCOM) research group. SnT carries out interdisciplinary research in secure, reliable and trustworthy ICT systems and services, often in collaboration with industrial, governmental or international partners. For further information, you may refer to www.securityandtrust.lu

The SIGCOM research group is headed by Prof. Symeon Chatzinotas, and mainly carries out research activities in the areas of signal processing for wireless communication systems, including satellite communications, and is currently expanding its research activities towards quantum information systems. Use cases of interest include IoT verticals, unmanned aerial vehicles, integrated satellite-space-terrestrial networks, quantum communications and key distribution, spectrum management and coexistence, tactile Internet, and autonomous transportation. Furthermore, our activities are experimentally driven and supported by the SDR CommLab, the SDN Lab, the 6G-Space Lab, our SW Simulators, and our OTA Facilities. For further information, you may refer to https://wwwen.uni.lu/snt/research/sigcom

We’re looking for people driven by excellence, excited about innovation, and looking to make a difference. If this sounds like you, you’ve come to the right place!

This is a fully funded position with an original duration of 2 years with a possibility to extend up to 5 years upon the performance and funding availability. The successful candidate is expected to develop safe and robust machine learning-based solutions for multilayer Ground-Air-Space 6G networks. The design strategies will be optimized for 1) Distributed RAN resource allocation, 2) 3D mobility management and routing and 3) risk minimization to guarantee constraints in dynamic topology of multilayer 6G environment.

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

• Work on an emerging research topic of rule-based/physics-inspired ML for 6G networks
• Contribute to the National FNR CORE project “RUTINE: Distributed and Risk-aware Multi-Agent Reinforcement Learning for Resources and Control Management in Multilayer Ground-Air-Space Networks”
• Disseminate results through scientific publications in the top-tier venues
• Coordinating research projects and preparing project deliverables
• Preparing new research proposals to attract industrial, national and European projects
• Providing assistance in the supervision of PhD students

Qualification: The candidate should possess a PhD degree or will graduate soon in Electrical Engineering, Computer Science, or equivalence.

Experience:

• Should have published at least 2 journal papers in top 10% international journals of the field
• Proven track-record on one or some of the following areas: wireless communications technologies, stochastic optimization, multiagent and reinforcement learning, ML/AI for communications
• Strong programming skills in MATLAB, Python, R or C++
• Highly committed, excellent team-worker, and strong critical thinking skills
• Excellent written and oral communication skills in English

• Exciting infrastructures and unique labs. At SnT’s two campuses, our researchers can take a walk on the moon at the LunaLab, build a nanosatellite, or help make autonomous vehicles even better
• The right place for IMPACT. SnT researchers engage in demand-driven projects. Through our Partnership Programme, we work on projects with more than 55 industry partners
• Be part of a multicultural family. At SnT we have more than 60 nationalities. Throughout the year, we organise team-building events, networking activities and more