MSCA-PF: Joint application at the University of Granada. Department of Software Engeneiring.
Professor Mª Belén Prados SUárez, from the Department of Software Engeneiring 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 Visual Information Processing Group (VIPG) at the University of Granada is an established research unit with over 35 years of expertise in digital signal processing, computer vision, and machine learning. Historically recognized for its work in image restoration and reconstruction, the group has evolved into a leader in applying Deep Neural Networks (DNNs) to complex inverse problems and large-scale data analysis. VIPG’s core strength lies in its ability to develop efficient algorithms for information processing, a heritage derived from its pioneering work in image compression and representation where optimizing computational resources is a primary constraint.
Currently, the group leverages its extensive experience in neural architectures to address the pressing challenges of AI sustainability and privacy. By focusing on the optimization of local Large Language Models (LLMs), VIPG aims to quantify and reduce energy consumption while establishing robust privacy-preserving frameworks. The group’s members belong to the departments of Computer Science & AI and Software Engineering, fostering a multidisciplinary approach that combines advanced mathematical modelling with software optimization. With a track record of over 50 international and national projects and hundreds of publications in top-tier journals, VIPG provides a high-level academic environment. Its global network includes long-standing partnerships with institutions like Oxford and Northwestern University, ensuring that MSCA fellows are integrated into a cutting-edge, internationally-connected research ecosystem focused on trustworthy and green AI.
URL: https://vip.ugr.es/
Project description:
Title: Sustainable and Private Generative AI: Optimizing Local LLMs for Green and Secure Computing (GreenPriv-LLM)
Description: The rapid integration of Large Language Models (LLMs) into digital workflows has raised two critical concerns: the massive energy footprint of these models and the vulnerability of sensitive data processed by cloud-based commercial providers. This research project, GreenPriv-LLM, aims to establish a comprehensive framework for the development of sustainable and privacy-preserving AI interfaces through the optimization of local LLM deployment.
The research line focuses on three core pillars:
a. Sustainability Analysis: A rigorous benchmarking of local LLMs (such as Llama, Mistral, or specialized small language models) to quantify energy consumption across different hardware configurations and quantization levels. This data will be used to create extrapolation models to estimate the environmental impact of large-scale commercial architectures.
b. Privacy-by-Design: Evaluating the trade-offs between model performance and data security. By shifting processing from the cloud to local, decentralized environments, the project seeks to eliminate data leakage risks in sensitive sectors like healthcare or legal services.
c. Optimization Frameworks: Developing algorithmic strategies to reduce the carbon footprint of local inference without compromising reasoning capabilities. This involves exploring efficient fine-tuning techniques (e.g., LoRA) and hardware-aware optimizations.
The project aligns with the European Green Deal and the AI Act’s mandate for transparent and sustainable high-risk AI. Hosted by the VIP Group at the University of Granada, the fellow will leverage the group’s expertise in neural optimization and signal processing to deliver a paradigm shift: making Generative AI not only "smart" but also environmentally responsible and inherently secure.
Research Area:
- Information Science and Engineering (ENG)
For a correct evaluation of your candidature, please send the documents below to Professor Mª Belén Prados SUárez (belenps@ugr.es):
- CV
- Letter of recommendation (optional)
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