Signal processing and learning algorithms for intelligent wireless networks

The Networked Systems team, led by Prof. Sofie Pollin at KU Leuven, conducts high-quality research on intelligent and adaptive wireless networks. The group explores how communication, sensing, and computation can be seamlessly integrated to enable the next generation of networked intelligent systems.

Our research spans the full stack—from theoretical models and algorithms to experimental validation—with a particular focus on the interplay between signal processing, artificial intelligence, and hardware constraints. By combining insights from information theory, optimisation, and learning, we aim to develop systems that are robust, efficient, and aware of their environment.

Current research themes include:
- Integrated Sensing and Communication (ISAC) for joint environment perception and connectivity
- AI-driven signal processing and data-driven modeling for adaptive networks
- Distributed and edge learning for scalable intelligence
- Energy-efficient and resilient wireless systems leveraging new spectrum bands and architectures
- Theory and algorithms for network coordination and dynamic resource management

The group is embedded in the Department of Electrical Engineering (ESAT) at KU Leuven, one of Europe’s top institutions in ICT and systems research. The team collaborates closely with academic and industrial partners worldwide and is active in major European projects and international collaborations, providing an inspiring and multidisciplinary research environment.
Website unit

Project

We invite applications for a Postdoctoral Researcher to join the Networked Systems team at KU Leuven, working on fundamental and algorithmic aspects of signal processing and artificial intelligence for future wireless systems.

The successful candidate will contribute to advancing the theoretical foundations and algorithmic tools for learning, sensing, and communication in networked systems. Research topics may include, but are not limited to:

• Distributed learning and inference in wireless networks
• Signal processing for integrated sensing and communication (ISAC)
• AI-driven resource optimization and control
• Theoretical analysis of learning-enabled communication systems
• Algorithm design for energy-efficient and adaptive networks

You will work closely with PhD students and other postdoctoral researchers, contribute to publications in leading journals and conferences, and collaborate in European and national research projects. Opportunities exist to engage in experimental validation and system-level integration of your algorithms, as well as co-supervision of graduate students.

Profile

• PhD in Electrical Engineering or related field
• Strong background in at least one of the following: Signal processing and estimation; Machine learning and AI; Optimization and control algorithms; Information or communication theory)
• Solid analytical and mathematical skills
• Experience with Python, MATLAB, or similar tools
• Strong publication record in relevant fields
• Excellent written and oral communication skills in English
• Team-oriented mindset and motivation for collaborative, interdisciplinary research

Offer

Interested?

For more information, you can contact Prof. dr. ir. Sofie Pollin, mail: [emailprotected]

KU Leuven strives for an inclusive, respectful and socially safe environment. We embrace diversity among individuals and groups as an asset. Open dialogue and differences in perspective are essential for an ambitious research and educational environment. In our commitment to equal opportunity, we recognize the consequences of historical inequalities. We do not accept any form of discrimination based on, but not limited to, gender identity and expression, sexual orientation, age, ethnic or national background, skin colour, religious and philosophical diversity, neurodivergence, employment disability, health, or socioeconomic status. For questions about accessibility or support offered, we are happy to assist you at this email address.