AI-enhanced DSP for wireless communications

This PhD position is part of a collaboration between imec and KU Leuven under the supervision of Prof. Sofie Pollin (KU Leuven) and co-supervision of Prof. Claude Dessert (IMEC). The vacancy is hosted primarily at imec (Leuven, Belgium). Applications must be submitted through the imec website.Imec is a world-leading research and innovation hub in nanoelectronics and digital technologies. Working closely with KU Leuven, imec combines fundamental research with industrial partnerships to develop the technologies that shape future applications.The research centre WaveCoRE in the Department of Electrical Engineering (ESAT) of KU Leuven focuses on wireless communication fundamentals and systems. In the WaveCoRE, the Networked Systems group led by Prof. Sofie Pollin covers research on various fields of wireless communications and networking such as Cell-Free Massive MIMO, Non-Terrestrial Networks (NTN), Internet of Things (IoT), Joint Communication and Sensing, Machine Learning-based Signal Processing, and Simultaneous Wireless Information and Power Transfer (SWIPT), etc.ProjectWireless systems are designed combining analog front-ends and digital baseband or physical layer (PHY) processing. Traditionally, PHY DSP blocks are created by expert knowledge from communications theory based on how the system behaves and how signals should be processed. This can include filters, FFTs, modulation, coding, multiple-antenna operations, hardware non-ideality compensation and a few other blocks.More recently, artificial intelligence has been appearing across many domains. In some fields it can lead to solutions un-attainable by expert models, while in other fields it simply cannot improve the performance of traditional solutions. Among many other domains, AI or ML-based solutions are also being investigated for PHY processing.In this PhD, you will take a critical look at those developments. By extensively reviewing the recent state-of-the-art on ML-based PHY solutions, you will identify the most promising blocks where AI solutions have the potential to out-perform traditional approaches - either in performance or in complexity - but also clarify which components cannot be improved, based on understanding performance and complexity bounds for the different approaches.Typically, AI-based solutions are more relevant for non-linear problems, hard-to-model behaviors, or when known solutions have excessive complexity due to the problem size. You will refine those criteria, identifying relevant domains for AI-enhanced PHY. They could come from non-ideal hardware effects, interference between multiple systems, complex mobile multi-path environments, or other sub-problems.In a second phase, you will select a few DSP blocks where AI-based approaches are most promising from this analysis and propose new designs able to out-perform traditional solutions. You will develop and test AI-based solutions for those components, assess their benefits based on extensive and realistic end-to-end simulations, and optimize them for the best performance/complexity trade-offs. By doing so, you will enable hybrid PHY implementations combining traditional and AI-based blocks for the best overall performance.You will be part of a large imec community working on the research, implementation and prototyping of future communications systems with experts in wireless communication, signal processing, digital, analog and mm-wave design, and machine learning. This is a unique opportunity to develop innovative, multi-disciplinary technology and shape future wireless networks. You will publish your research in top-level journals and conferences.orks. You will publish your research in top-level journals and conferences. Profile We are looking for highly motivated Ph.D. researchers with expertise in wireless communications and signal processing. The applicant should hold a master's degree in electrical engineering, Telecommunication Engineering, or relevant fields. The applicant should also meet the minimum eligibility criteria for enrolling as a Ph.D. student at KU Leuven, namely, having exceptional grades as well as proficiency in English. The applicant should have knowledge of channel modelling and MIMO is a plus. Proficiency with Matlab or Python. Additionally, the applicant should have strong interpersonal skills and the ability to work in an international team. Offer Type of work: 20% literature and theory, 60% modelling and simulation, 20% design/experimentalA Ph.D. scholarship for up to four years (subject to positive intermediate evaluations)An inclusive research environment, working on the intersection between theory and implementation, in a very multidisciplinary research environment. A Ph.D. title from a highly ranked university, ranked #50 in Best Global Universities according to US News. Opportunity to build up an international network, participation in international conferences and collaborations.Competitive salary and funding Access to imec’s world-class facilities and collaboration with leading expertsMore details and application on the imec website Interested? Applications Must Be Submitted Via The Imec Websitehttps://www.imec-int.com/en/work-at-imec/job-opportunities/ai-enhanced-dsp-wireless-communicationsThe reference code for this position is 2026-015. Mention this reference code on your application form.For more information, you can contact Prof. dr. ir. Sofie Pollin, mail: sofie.pollin@kuleuven.be or Prof. dr. ir. claude.desset@imec.beYou can apply for this job no later than December 11, 2025 via the online application toolKU 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. Sollicitatieprocedure Arbeidsvoorwaarden Loopbaanmogelijkheden Heb je een vraag over de online sollicitatieprocedure? Raadpleeg onze veelgestelde vragen of stuur een e-mail naar solliciteren@kuleuven.beSolliciteer voor deze functie