OFFER DEADLINE30/09/2022 14:00 - Europe/Brussels
EU RESEARCH FRAMEWORK PROGRAMMEHE / MSCA
ORGANISATION/COMPANYInternational Research Projects Office
DEPARTMENTPromotion and Advisory Unit
Professor Angel M. Gómez García, 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 2022 at this University. Please note that applicants must comply with the Mobility Rule (for more information about the 2022 call, please consult: http://sl.ugr.es/0cmA).
Brief description of the institution:
The University of Granada (UGR) was founded in 1531 and is one of the largest and most important universities in Spain. With over 60,000 undergraduate and postgraduate students and 6,000 members of staff, the UGR offers over 70 undergraduate degrees, 100 master’s degrees (9 of which are international double degrees) and 28 doctoral programmes via its 127 departments and 22 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 improving 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 2021 edition of the ARWU places the UGR in 201-300th position in the world and as the second highest ranked university in Spain (http://sl.ugr.es/0cmF), reaffirming its position as an institution at the forefront of national and international research. The UGR stands out in the specialties of Library & Information Science (position 36); Food Science & Technology (39) and Hospitality & Tourism Management (51-75), according to the latest edition of this prestigious ranking by specialties (http://sl.ugr.es/0bSp). A little lower in the ranking, the UGR also stands out in Mathematics (76-100) and Mining & Mineral Engineering (76-100).
Additionally, the UGR has 7 researchers who are at the top of the Highly Cited Researchers (HCR) list (http://sl.ugr.es/0cmD), most of these related to the area of Computer Science. It is also well recognized for its web presence (http://sl.ugr.es/0a6i), being positioned at 54th place in the top 200 Universities in Europe.
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 last two Framework Programmes, the UGR has obtained a total of 67 projects, with total funding of 18.029 million euros, and for H2020, 119 projects with a total funding of around 29.233 million euros.
Brief description of the Centre/Research Group:
The Signal Processing, Multimedia Transmission and Speech/Audio Technologies (SigMAT) Research Group started in 2012 with the goal of producing transformative breakthroughs in fields ranging from speech technologies, multimedia & audio processing, and applied machine learning. Our research vision not only strives for academic excellence but also for disseminating knowledge and harnessing new ideas and innovations for the benefit of society. Training researchers is a key element of our work, in which we hold a large experience, with multiple PhD thesis successfully defended in the last 10 years. Former SigMAT students are now senior scientists in different positions both in academia and industry. Interests of the SIGMAT Group are mainly (but not only) focused on the following topics:
- Research, innovation and development of speech technologies: speech enhancement, recognition, coding, synthesis (silent and thought speech) and biometrics (speaker recognition and antispoofing).
- Development of robust transmission techniques of multimedia information: speech, images, and video.
- Research dissemination towards other fields of signal processing application, such as array signal processing (beamforming), ultrasonics or proteomics.
- Transfer of the engineering knowledge created by our researchers by developing partnerships with industry through the creation of new ventures and collaborations with corporations.
The use of deep learning approaches in the Signal Processing field is finally showing a trend towards a rational use. After a period of effervescence where research activity seemed to focus on seeking old problems to apply solutions entirely based on neural networks, we have reached a more mature stage where integrating approaches are on the rise. These approaches gather the best from each paradigm: on the one hand, the knowledge and elegance of classical signal processing and, on the other, the huge ability to model and learn from the data which is inherent to deep learning methods. In this project we aim towards a new signal processing paradigm, where classical and deep learning techniques not only collaborate, but fuse themselves. In particular, we focus on two objectives: 1) the development of deep learning architectures based on or inspired by signal processing schemes, and 2) the improvement of current deep learning training methods by means of classical techniques and algorithms, particularly, by exploiting the knowledge legacy they treasure. These innovations are applied to two scientifically and socially relevant topics in which the research group has been working for years. The first one is the enhancement of speech signal acquired under acoustic adverse conditions (e.g., noise, reverberation, other speakers, …), which is of great interest for current communications, home assistants and other hands-free devices. The second one is the development of anti-fraud measures for biometric voice authentication, in which banking corporations and other large companies are strongly interested.
- Information Science and Engineering (ENG)
For a correct evaluation of your candidature, please send the documents below to Professor Angel M. Gómez García (firstname.lastname@example.org):
- Letter of recommendation (optional)
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