Professor Luz García Martínez, from the Department of Signal Theory, Telematics and Communications at the University of Granada, welcomes postdoctoral candidates interested in applying for a Marie Skłodowska-Curie Postdoctoral Fellowship (MSCA-PF) in 2026 at this University. Please note that applicants must comply with the Mobility Rule (for more information about the 2026 call, please consult this link).

Brief description of the institution:

The University of Granada (UGR), founded in 1531, is one of the largest and most important universities in Spain. With more than 57,000 undergraduate and postgraduate students and almost 7,000 members of staff, the UGR offers 97 undergraduate degrees, 157 master’s degrees (7 of which are double degrees) and 28 doctoral programmes via its 124 departments and nearly 50 centers. Accordingly, the UGR offers one of the most extensive and diverse ranges of higher education programmes in Spain.

The UGR has been awarded with the "Human Resources Excellence in Research (HRS4R)", which reflects the institution’s commitment to continuously improve its human resource policies in line with the European Charter for Researchers and the Code of Conduct for the Recruitment of Researchers. The UGR is also internationally renowned for its excellence in diverse research fields and ranked among the top Spanish universities in a variety of ranking criteria, such as national R&D projects, fellowships awarded, publications, and international funding.

The UGR is one of the few Spanish Universities listed in the Shanghai Top 500 ranking - Academic Ranking of World Universities (ARWU). The 2025 edition of the ARWU places the UGR in 301-400th position in the world and as the 3-8 highest ranked University in Spain, reaffirming its position as an institution at the forefront of national and international research. From the perspective of specialist areas in the ARWU rankings, the UGR is outstanding in Mathematics, Artificial Intelligence and Dentistry & Oral Sciences (ranked between 51th-75th position), Computer Science & Engineering, Education and Hospitality & Tourism Management (between 76-100th position), and in the areas of Food Science & Technology and Business Administration (between 101-150th position). A little lower in the ranking, the UGR also stands out in the areas of Earth Sciences, Law, Management, Nursing, Psychology and Statistics, in which the UGR is positioned in the 151-200th position.

Additionally, the UGR counts with 4 researchers at the top of the Highly Cited Researchers (HCR) list, most of them related to the Computer Science and Mathematics scientific areas. It is also well recognised for its presence in the top 200 Universities in Europe at 83th place.

Internationally, the University of Granada is firmly committed to its participation in the calls of the Framework Programme of the European Union. For the duration of the prevoius Framework Programme, Horizon 2020, the UGR obtained a total of 124 projectswith a total funding of more than €30 million. For the current Framework Programme, Horizon Europe, the UGR has obtained 136 projects, so far, with a total funding of more than €38 million.

Brief description of the Centre/Research Group:

The SMART DAS LAB, part of the TIC-270 research group (https://tic270.ugr.es/) at the University of Granada (Spain), offers an attractive and internationally oriented research environment at the forefront of distributed acoustic sensing (DAS), signal processing, and artificial intelligence. The group operates a unique city-scale living lab that transforms standard telecommunication optical fibers into dense arrays of virtual sensors, enabling continuous, real-time monitoring of urban dynamics.

Its experimental infrastructure, deployed in the city center of Granada, comprises operational telecom fibers spanning several kilometers and interrogated using state-of-the-art high-fidelity DAS technology. This platform provides direct access to large-scale, real-world datasets capturing traffic flows, mobility patterns, and urban activity, creating outstanding opportunities for impactful, data-driven research.

The group combines strong expertise in advanced signal processing, feature engineering, and machine learning, with particular emphasis on developing robust and interpretable models tailored to DAS data. Research spans smart city monitoring, environmental sensing, and intelligent infrastructure systems.

SMART DAS LAB maintains close collaboration with industry stakeholders, including telecom operators and sensor manufacturers, facilitating access to real deployments and promoting effective knowledge transfer. The lab offers excellent conditions for high-impact research, interdisciplinary collaboration, and advanced training within a vibrant European research ecosystem.

Project description:

Learning from Fiber: AI for Urban Sensing with DAS

The successful applicant will join an active and forward-looking research line aimed at advancing distributed acoustic sensing (DAS) for urban environments within a real-world, city-scale experimental platform. The project focuses on enhancing current traffic monitoring capabilities while exploring new sensing paradigms that extend the scope of DAS in complex urban settings.

A central research direction addresses the integration of multiple fiber links to improve spatial coverage and robustness. In this context, the project will investigate advanced strategies for coordinated interrogation of telecommunication fibers, and the fusion of their outputs into consistent representations of urban dynamics. This line aims to move towards more flexible, scalable, and reconfigurable sensing architectures.

In parallel, the project will explore the detection of subtle and non-conventional vibration sources embedded in urban environments. This exploratory direction seeks to assess the broader potential of DAS beyond mobility monitoring, including its capacity to capture fine-grained activity patterns that remain largely unobserved with current sensing technologies.

Methodologically, the research will combine advanced signal processing, spatio-temporal modeling, and machine learning techniques to address challenges such as noise variability, overlapping sources, and transferability across locations and sensing conditions.

Overall, the project offers a balanced and ambitious research agenda, combining methodological innovation with exploratory applications, and strong potential for scientific impact and real-world relevance in intelligent and sustainable urban systems.

Research Area:

• Information Science and Engineering (ENG)

For a correct evaluation of your candidature, please send the documents below to Professor Luz García Martínez (luzgm@ugr.es):

• CV
• Letter of recommendation (optional)