We are looking for highly motivated PhD researchers with an interest in non-terrstrial communication systems design. The applicant should
1. have a master’s degree in Electrical Engineering or Telecommunication Engineering,
2. be ranked within the top 10% of their class in MSc and BSc, and have exceptional grades,
3. have has strong communication skills and is fluent in English,
4. have a solid background in wireless communication and networking fundamentals,
5. have strong interpersonal skills and the ability to work in an international team.
6. Experience in AI-enabled signal processing and machine learning algorithms is a valuable addition.
As climate change intensifies, clear-air turbulence in aviation becomes more severe, and natural disasters occur more frequently. Even with the current typical 10-day weather forecast in the troposphere (less than 20 km), the exact spatiotemporal mechanisms through which the Earth’s low altitudes (ELA) (less than or equals 50 km) impact weather patterns remain insufficiently understood. In-situ sensing in ELA offers an opportunity to extend weather forecasts far beyond the current 10-day range, improve ozone observation, and enhance cosmic radiation monitoring. The rapid advancements in rotary-wing and fixed-wing unmanned aerial vehicle (UAV) technology make them a promising solution to densify ELA monitoring. However, expanding the density of meteorological sensors in the ELA to bridge the spatiotemporal meteorological gaps presents major fundamental challenges. First, the vast volume and heterogeneity of data generated by airborne UAV and WB sensors strain efficient raw data transfer and require significant computational resources for centralized processing. Second, the existing centralized, terrestrial-based control infrastructure cannot scale with the increasing number of airborne sensors due to bandwidth and coverage constraints. These challenges are further exacerbated due to the limited energy budget and computational resources of the meteorological aerial sensor.In its first phase, this PhD project aims to design an ultra-efficient, semantic-aware distributed aerial network tailored for aerial nodes’ control, featuring semantic communication to maximize energy/spectrum efficiency, sending control semantics (e.g., stay/change/continue path) instead of positional information. Semantic-ware PHY-MAC cross-layer design will be studied in the context of M2M communication (i.e., UAVs and WBs) for real-time control. In the second phase, seamless integration of sensing, computation, and communication functionalities for context-aware self-organized aerial networks will be investigated.The research group WaveCoRE in the Department of Electrical Engineering (ESAT) is dedicated to advancing the fields of electromagnetic theory, wave propagation, microwave and millimeter-wave circuits, and wireless systems. Within WaveCoRE, the Networked Systems team covers research on several fields of wireless communications, including non-terrestrial UAV and satellite networks, next-generation radio access networks, sustainable Internet of things, joint communication and sensing, as well as machine learning-based signal processing.We offer:
7. A PhD scholarship for up to four years (subject to positive intermediate evaluations). If the applicant is non-EER, up to 1 year of pre-doc will also be supported.
8. An exciting research environment, working on the intersection between theory and implementation in a very multi-disciplinary research environment.
9. A PhD title from a highly ranked university (#1 in Europe in terms of scientific innovation) after approximately 4 years of successful research.
10. A thorough scientific education, the possibility of becoming a world-class researcher.
11. A KU Leuven affiliation, one of the largest research universities in Europe.
12. You will be working on a state-of-the-art topic with state-of-the-art laboratories.
13. The possibility to participate in international conferences, workshops and collaborations with top EU research teams.