Doctoral researcher in Dynamic Topology-oriented Machine Learning for Future Satellite Communications

The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character.

The Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services.

We play an instrumental role in Europe by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services & Applications.

The SigCom research group of SnT, headed by Prof. Symeon Chatzinotas, focuses on wireless/satellite communications and networking. The research areas focus on the formulation, modeling, design, and analysis of future 6G communication networks that are capable of supporting new services for digital ecosystems. Use cases of interest include Security and Efficient Wireless Communication Solutions, IoT verticals, Unmanned Aerial Vehicles, Integrated Satellite-Space-Terrestrial Networks, Quantum Communications and Key Distribution, Spectrum Management and Coexistence, Tactile Internet, Earth Observation, and Autonomous Transportation. As far as technical enablers are concerned, we leverage expertise on advanced technologies including semantic/task-oriented data processing, signal processing, network resource management to improve the performance of the future wireless communication systems. Finally, due to the large-scale nature, complexity, and heterogeneity of 6G networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and supported by the COMMLab, the 6GSPACE Lab, the HybridNetLab, the QCILab, the TelecomAILab, the CSATLab, our SW Simulators, and our Facilities. For further information, you may refer to

The successful candidate will join the SIGCOM Research Group, led by Prof. Symeon Chatzinotas. This PhD project aims to develop machine learning (ML) models and optimization algorithms specifically designed for highly dynamic satellite communication (SatCom) systems that can handle networks of varying sizes and configurations without requiring retraining from scratch, while maintaining robustness to changes in node order and network topologies.

You will be required to perform the following tasks:

• Carrying out research in the predefined areas
• Implement and open-source proof-of-concept software tools
• Collaborate with other researchers in SigCom and disseminate the outputs at conferences, workshops organized by the consortium
• Disseminate results through scientific publications
• Present results in well-known international conferences and workshops
• Participating in outreach events related to AI and SatCom, inspiring young generations to be interested in related topics

For further information, please contact Prof. Symeon CHATZINOTAS at or Dr. Ti Ti NGUYEN at

Qualification: The candidate should possess an MSc degree or equivalent in Mathematics, Telecommunications and Computer Science.

Experience: The ideal candidate should have some knowledge and/or experience in several of the following topics:

• Experience with Machine Learning, particularly Graph Neural Networks, Transfer Learning, Deep Reinforcement Learning, and Transformer-based models, including hands-on implementation
• Strong understanding of machine learning models and their development
• Strong analytical, problem solver, and programming skills, e.g. Python, Matlab, are preferred
• Knowledge in Non-Terrestrial Networks and Semantic Communications is a plus

Prior proven experience in data-driven innovation projects is an asset as well as having prior research publications in high-ranking journals or in international conference proceedings. Most importantly, you should be curiosity driven and willing to constantly learn new things

Language Requirements:

Applicants must demonstrate at least B2-level proficiency in the language of their thesis. For details and accepted certificates, please visit the Application for admission – Doctoral Candidates.

• Multilingual and international character. Modern institution with a personal atmosphere. Staff coming from 90 countries. Member of the "University of the Greater Region" (UniGR)
• A modern and dynamic university. High-quality equipment. Close ties to the business world and to the Luxembourg labour market. A unique urban site with excellent infrastructure
• A partner for society and industry. Cooperation with European institutions, innovative companies, the Financial Centre and with numerous non-academic partners such as ministries, local governments, associations, NGOs …

Applications should include:

• Curriculum Vitae
• For each degree received or currently enrolled in, the degree, institution name, city, and country, and date/expected date of graduation
• Title and short summary of final thesis
• If available, link to GitHub repository including completed open-source projects
• Cover letter presenting your motivation for this doctoral thesis topic, and explaining how your qualifications and aspirations align with its academic focus
• Transcript of all modules and results from university-level courses taken

Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by Email will not be considered.

All qualified individuals are encouraged to apply. In line with our values, the University of Luxembourg promotes an inclusive culture. We encourage applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students.

General information:

• Contract Type: Fixed Term Contract 36 Month (extendable up to 48 months if required)
• Work Hours: Full Time 40.0 Hours per Week
• Location: Kirchberg Campus
• Internal Title: Doctoral Researcher
• Job Reference: UOL07930

The yearly gross salary for every PhD at the UL is EUR full time).