PhD Positions in Wireless Spectrum Data Research – SpecX MSCA DN
(ref. BAP
Laatst aangepast: 12/11/25
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.
KU Leuven coordinates the SpecX MSCA Doctoral Network, a Horizon Europe consortium that will recruit 15 doctoral researchers across several partner institutions in Europe. We aim to train 15 talented PhD students in the field of large-scale spectrum analytics, wireless communication and IoT connectivity. Each position corresponds to one of the 15 dedicated research topics within the network, hosted by different academic and industrial partners.
More information about the full training programme and all available positions can be found via the central application portal. Candidates should apply through that link and select the position relevant to them.
Project
The selected candidates will join SpecX, a Marie Skłodowska-Curie Doctoral Network (MSCA-DN) funded by the European Union under Horizon Europe. The network will recruit 15 doctoral researchers across several leading universities, research institutes, and industrial partners in Europe.
SpecX focuses on the future of large-scale spectrum sensing, wireless communication, and intelligent IoT connectivity, addressing the growing need for efficient use of the radio spectrum as demands for 5G, 6G, and massive IoT continue to increase. The project brings together expertise in radio frequency engineering, signal processing, embedded systems, machine learning, and networked communication.
Each PhD position corresponds to a dedicated research topic within the consortium. All doctoral researchers will benefit from joint supervision, network-wide training schools, and research visits ("secondments") to partner institutions in both academia and industry. The programme offers a unique opportunity to conduct high-impact research while developing transferable skills in an international, interdisciplinary setting.
The 15 open positions:
DC1: Low-power IoT sensing at high frequency bands
* Host: IMDEA Networks Institute, Madrid, Spain
* Main supervisor: Prof. Joerg Widmer [IMDEA Networks]
* Co-supervisors/mentors: Prof. M. Petrova [RWTH], Dr. T. Otim [IMDEA], and Dr. X. Costa-Perez [NEC]
* Required profile: Telecommunication, Electrical Engineering, Computer Science
* Desirable skills/interests: Signal processing, wireless communications, hands-on experience with hardwares
* Objectives: Low-power RF front-end design to monitor mm-wave spectrum for IoT communication and sensing applications with orders of magnitude less energy consumption than current solutions. Leverage large bandwidth at mm-wave to deploy several mm-wave IoT devices in dense deployments that can coexist for performing spectrum sensing.
DC2: Physics-Informed AI-empowered aerial and terrestrial distributed sensing
Host: KU Leuven, Belgium
* Main supervisor: Prof. Hazem Sallouha [KUL]
* Co-supervisors/mentors: Prof. M. Matinmikko-Blue [OULU], Dr. R. Martinez [KUL], and Dr. J. Buysse [Citymesh]
* Required profile: Telecommunications, Electrical Engineering
* Desirable skills/interests: Wireless communications, signal processing, optimisation, machine learning, as well as programming and implementation skills
* Objectives: To design sensors and a data acquisition system for the experimental 5D assessment of the spectrum (i.e., frequency, time, and 3D spatial measurement). The data acquisition system will coherently measure spectrum emitters in aerial or terrestrial wideband settings, boosted by AI-data augmentation for extrapolating spectrum patterns from multiple sources. To design a scalable computing framework using a physics-informed neural network for distributed spectrum analysis with sparse aerial and dense terrestrial sensors for enhanced 3D spectrum use prediction.
DC3: RF-sensing for ambient IoT devices and coexistence with legacy devices
* Host: IMDEA Networks Institute, Madrid, Spain
* Main supervisor: Prof. D. Giustiniano [IMDEA]
* Co-supervisors/mentors: Prof. P. Casari [UNITN] & Dr. T. Otim [IMDEA], and Dr. A. Rahman [ISRD]
* Required profile: Electrical Engineering, Computer Science, and Embedded Systems.
* Desirable skills, interests and background: Wireless communication, embedded systems, hardware design, signal processing
* Objectives: To perform spectrum measurements in the radio access network that can identify spurious RF transmissions originating from low-cost Ambient IoT devices. To design spectrum allocation mechanisms that take into account these interference patterns to design new spectrum allocation schemes that allow for a large number of Ambient IoT devices to coexist with battery-powered wireless devices.
DC4: Drone-hosted mobile spectrum sensing and cells for 6G
* Host: RWTH Aachen University, Germany
* Main supervisor: Prof. M. Petrova [RWTH]
* Co-supervisors/mentors: Joerg Widmer [IMDEA], Dr. L. Simić [RWTH], and Dr. A. Saavedra [NEC]
* Required profile: Electrical Engineering, Telecommunications Engineering, Computer Science or equivalent disciplines
* Desirable skills, interests and background: Wireless communication, embedded systems, signal processing, and fundamentals of networking.
* Objectives: To achieve on-device spectrum sensing using on-board sensors of mobile BSs, empowered by embedded deep learning algorithms; to propose an analytical model for the cell planning of drone-hosted mobile BSs based on user location and the coverage and interference map obtained from spectrum sensing. To study the trade-off between the physical adaptation of the BSs and the degradation of the system performance in mobile scenarios. To experimentally exploit drone-hosted mobile cells for 6G networks.
DC5: Anomaly analytics in geospatial spectrum data
* Host: XYZT, Belgium
* Main supervisor: Dr. B Adams [XYZT],
* Co-supervisors/mentors: Prof. H. Sallouha [KUL], and Dr. R. Martinez [KUL]
* Required profile: Telecommunications, Electrical Engineering, computer science
* Desirable skills/interests: Data analysis, data and signal processing, optimisation, programming & implementation skills.
* Objectives: To improve state-of-the-art algorithms for feature extraction, anomaly detection, and classification. To study how to incorporate expert feedback into a semi-supervised learning model, and how to efficiently compress and run the model on embedded devices. To combine heterogeneous data streams for wideband and narrowband cooperative and non-cooperative sensors.
DC6: Spectrum sensing for edge resource analytics
* Host: Consorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT), Italy
* Main supervisor: Dr. I. Tinnirello [CNIT]
* Co-supervisors/mentors: Prof. M. Petrova [RWTH], Dr. A. Rahman [ISRD]
* Required profile: Electrical Engineering, computer science, embedded systems
* Desirable skills, interests and background: Wireless communication and signal processing, wireless networking and protocols, mathematical modelling and analysis, algorithm design, estimation theory, machine learning, embedded hardware.
* Objectives: Identification of the functions on the edge infrastructures (e.g., resource allocation, anomaly detection, traffic forecast, SW/HW components) that can benefit from the availability of spectrum sensing analytics. Design of techniques and methods to leverage sensing information for improving QoS. Integration of spectrum data analytics in edge infrastructure.
DC7: Sensing-capable disaggregated 6G radio traffic analytics
* Host: RWTH Aachen University, Germany
* Main supervisor: Prof. M. Petrova [RWTH]
* Co-supervisors/mentors: Prof. S. Pollin [KUL] & Dr. L. Simić [RWTH], and Dr. B. Adams [XYZT]
* Required profile: Electrical Engineering, Telecommunications Engineering, Computer Science or equivalent disciplines
* Desirable skills/interests: Deep learning, tiny machine learning, TensorFlow lite micro, embedded system, wireless communications (the applicant should be proficient in at least two of the skills).
* Objectives: To study and identify enablers for realising and integrating a sensing functionality in the future RAN and disaggregated components. Study techniques for both data-driven and predictive dynamic spectrum allocation and sharing. To identify how to integrate spectrum sensing mechanisms in telecom edge infrastructure.
DC8: Spectrum resource allocation for integrated communication and sensing
* Host: Consorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT), Italy
* Main supervisor: Prof. S. Bartoletti [CNIT]
* Co-supervisors/mentors: Prof. S. Mazuelas [BCAM] & Prof. G. Bianchi [UNITV], and Dr. A. Saavedra [NEC]
* Required profile: Telecommunications, Electrical Engineering, Computer Science
* Desirable skills/interests: Wireless communication, statistical signal processing, algorithm design, optimization and estimation theory, hands-on experience or interest in measurement/test equipment.
* Objectives: To study and develop strategies for allocating spectrum resources in integrated sensing and communication. Spectrum resource allocation should consider both the accuracy, efficiency and robustness of sensing jointly with communication performance.
DC9: Network analytics of massive Ambient IoT deployments
* Host: Consorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT), Italy
* Main supervisor: Prof. Paolo Casari [UNITN]
* Co-supervisors/mentors: Prof. K. S. Yildirim [UNITN], Dr. Gianluca Verin [APEIROON]
* Required profile: Electrical Engineering, Telecommunications, Computer Science
* Desirable skills/interests: Wireless networking, signal/array processing, machine learning, optimization, hands-on experience with hardware and systems.
* Objectives: To infer the status of distributed, heterogeneous massive IoT deployments based on the joint analysis of spectral information. To implement orchestration policies for computation task allocation with Ambient IoT nature of IoT devices, optimising the performance of status inference, using principles of network virtualisation, computing task placement, and machine learning.
DC10: Network management solutions for Public Protection and disaster relief scenarios
* Host: APEIROON, Italy
* Main supervisor: Prof. F. Granelli [UNITN]
* Co-supervisors/mentors: Mr. Antonio Fin [APEIROON, Prof. M. Matinmikko-Blue [OULU]
* Required profile: Telecommunication engineering, applied mathematics, electrical engineering, and computer science.
* Desirable skills/interests: Signal processing, machine learning, applied optimisation, wireless network management, and interest in robotic communication systems or networked autonomous systems for public safety.
* Objectives: To investigate the prioritisation and reliability network hardening strategies for PPDR scenarios, including heterogeneous communication environments integrating both human and robotic agents. To propose a network orchestration framework coordinated with the spectrum slicing protocols for efficient provisioning of network slices that can dynamically support mission-critical users and networks of autonomous robots (e.g., drones, ground units) assisting in emergency and disaster-relief operations.
DC11: Positioning of non-cooperative transmitters and their pattern of movements
* Host: IMDEA Networks Institute, Madrid, Spain
* Main supervisor: Prof. D. Giustiniano [IMDEA]
* Co-supervisors/mentors: Prof. M. Zheleva [AlbanyU] & Dr. G. Santaromita [IMDEA], and B. Adams [XYZT]
* Required profile: Electrical Engineering, Computer Science, and Embedded Systems.
* Desirable skills/interests: Signal processing, localization theory, machine learning, applied optimisation, embedded programming.
* Objectives: Feature extraction and distributed algorithms to localise any wireless transmitter in mobile environments that does not collaborate (passive positioning), and its implementation in 5G cellular infrastructure. Extraction of analytics from multiple target users.
DC12: Geo-statistical analysis of spectrum data for coverage/performance maps
* Host: Telefonica I+D, Spain
* Main supervisor: Dr. A. Lutu [TID]
* Co-supervisors/mentors: Prof. P. Serrano [UC3M], Prof. I. Tinnirello [CNIT]
* Required profile: Telecommunication engineering, applied mathematics, electrical engineering, and computer science.
* Desirable skills/interests: Signal processing, machine learning, applied optimisation.
* Objectives: To analyse large-scale data that is reliable and collected from spectrum sensing methods. To contrast network-side planned radio coverage with the actual experience of the end-users and build anomaly detection approaches, traffic and user patterns forecast, answer what-if questions regarding the network deployment, etc., to help radio planning teams.
DC13: Spectrum-awareness empowered wireless systems for safety-critical applications
* Host: KU Leuven Campus Bruges, Belgium
* Main supervisor: Prof. T. Claeys [KUL]
* Co-supervisors/mentors: Joerg Widmer [IMDEA], Prof. D. Pissoort [KUL], and Dr. J. Buysse [Citymesh]
* Required profile: Telecommunication engineering, applied mathematics, electrical engineering, and computer science.
* Desirable skills/interests: Signal analysis, telecommunication, applied optimisation, safety-critical engineering
* Objectives: To identify the possible risks and threats of using wireless connections for safety-critical applications, such as those used in Industry 4.0 and drone operations. To develop a systematic and spectrum-aware approach for detecting and reacting to anomalies, with a particular focus on sensing and mitigating intentional or unintentional jamming in the wireless spectrum. To design and implement adaptive avoidance techniques that ensure reliable communication under adverse spectral conditions. To apply and validate the developed methods in industry-oriented case studies.
DC14: AI-embedded sensing for E-field exposure assessment
* Host: KU Leuven, Belgium
* Main supervisor: Prof. S. Pollin [KUL]
* Co-supervisors/mentors: Prof. S. Bartoletti [CNIT], Dr. R. Martinez [KUL], and Dr. J. Suárez-Varela [TID]
* Required profile: Telecommunication engineering, applied mathematics, electrical engineering, and computer science.
* Desirable skills/interests: Signal processing, wireless communication, machine learning, electromagnetic propagation.
* Objectives: To assess the E-field exposure of new-generation radios using software-defined-radio data acquisition systems and embedded AI analytics. To design low-complexity AI algorithms that can work with limited IQ signals data, and accurately extrapolate the total exposure in massive MIMO mobile networks, where time multiplexing and beamforming create complex exposure patterns that deviate from the mean exposure in traditional cellular networks. To experimentally test the proposed solution on embedded devices.
DC15: Spectrum management addressing policy-making and business stakeholders' claims
* Host: University of Oulu, Finland
* Main supervisor: Adj. Prof. M. Matinmikko-Blue [OULU]
* Co-supervisors/mentors: Prof. S. Mazuelas [BCAM] & Dr. A. w [OULU], and Dr. A. Lutu [TID]
* Required profile: Telecommunication engineering, applied mathematics, electrical engineering, and computer science.
* Desirable skills/interests: Wireless communications, telecommunication regulation, business ecosystems.
* Objectives: To study and develop a spectrum management framework that incorporates spectrum analytics as a service and considers requirements from spectrum policy-making and conflicting business stakeholders' agendas. To develop spectrum management techniques that make use of spectrum analytics to allow local 6G networks to access the radio spectrum on a shared basis. To translate research findings into relevant knowledge for regulatory bodies for policy making.
Profile
* We are looking for highly motivated Ph.D. researchers with interests in wireless communication, spectrum analytics, embedded systems, signal processing, machine learning, or related fields.
* The applicant should hold a master's degree in Electrical Engineering, Telecommunications, Computer Science, Applied Mathematics, or a closely related discipline.
* The applicant should also meet the minimum eligibility criteria for enrolling as a Ph.D. student having exceptional grades as well as proficiency in English.
* The applicant should have a background in wireless communication. The international publication held by the applicant will be a plus.
* Additionally, the applicant should have strong interpersonal skills and the ability to work in an international team.
* Moreover, specific MSCA eligibilty rules (see also on application website):
* Early Stage Rule: Applicants should be, at the time of recruitment by the host institution, in the first four years (full- time equivalent) of their research careers and have not yet been awarded a doctoral degree. This is measured from the date when they obtained the degree, which would formally entitle them to embark on a doctorate.
* Mobility Rule: At the time of recruitment, the applicant must not have lived in the country where the position is offered for more than 12 months in the previous 36 months.
Offer
* Attractive and competitive salary in accordance with the Marie Skłodowska-Curie Actions (MSCA) Doctoral Network regulations
* Additional family allowance (if applicable) and dedicated budget for research and training costs
* PhD funding for 36 months through the MSCA network (with potential for additional funding depending on host institution and national regulations)
* Opportunity to pursue a PhD degree at a leading European university within a collaborative, international network
* Comprehensive training programme including research-specific and transferable skills courses
* Opportunities for internships, secondments, and collaboration within academia and industry partners across Europe
* Active participation in workshops, conferences, and network-wide events to build professional and scientific connections
* Stimulating, multidisciplinary, and international research environment within a prestigious European training network
https://specx-
Interested?
For more information please contact Mrs. Marisa Veloso Ferreira, mail: or Mr. Hazem Wafa, mail:
You can apply for this job no later than January 30, 2026 via the online application tool
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.
Heb je een vraag over de online sollicitatieprocedure? Raadpleeg onze veelgestelde vragen of stuur een e-mail naar
av_timer
Tewerkstellingspercentage: Voltijds
location_city
Locatie: Leuven
timer
Solliciteren tot en met:
30/01/2026 23:59 CET
bookmarks
Tags: Elektrotechniek