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MSCA-PF: Joint application at the University of Granada. Department of Signal Theory, Networking and Communication.

International Research Projects Office

Hosting Information

Offer Deadline
EU Research Framework Programme


Organisation / Company
International Research Projects Office
Promotion and Advisory Unit
Is the Hosting related to staff position within a Research Infrastructure?

Contact Information

Organisation / Company Type
Higher Education Institute
Postal Code
Gran Vía de Colón, 48, 2nd floor


Professor José Camacho Páez, from the Department of Signal Theory, Networking and Communication 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:

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 (, 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 ( 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 (, most of these related to the area of Computer Science. It is also well recognized for its web presence (, 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 research group at the University of Granada is specialized in biostatistics, machine learning and multivariate analysis in omics data and other sources of complex data. The group has a dilated experience in the identification of biomarkers in different diseases such as obesity and cardiovascular disease or cancer, using cutting-edge techniques, among which OMICs (genomics to metabolomics) have a central position. The group includes experts in multivariate analysis and biostatistics and their application to real problems of optimization, machine learning and data analysis, including the processing of medical data. The research group has also developed the Multivariate Exploratory Data Analysis (MEDA) Toolbox in Matlab,, a set of multivariate analysis tools for the exploration of complex and Big Data sets. The MEDA Toolbox includes traditional exploratory plots based on Principal Component Analysis (PCA) or Partial Least Squares (PLS) with new methods specially designed for OMICs data analysis and extensions to Big Data.

We provide:

- Techniques, software tools and computer servers for data analysis, design of experiments, sample size computation, interpretation of results, identification of biomarkers, estimation of statistical significance and other similar capabilities for the treatment of omics or other data.

- The ability to use state-of-the-art tools, like PCA/PLS-DA, sparse methods, variable selection, ASCA, PERMANOVA, Design of Experiments, etc.

- The ability to design new algorithms tailored to the analysis problem at hand.

- The design of clinical studies, analysis of samples and interpretation of omics data.

Project description:

The Project is centered on the study of statistical inference (computation of significance through p-values and similar strategies) for the detection of biomarkers in omics experiments with a focus on human health research. We would like to work on the following topics:

-Disentangling the advantages/disadvantages of methods based on the False Discovery Rate in comparison to multivariate methods (ASCA, PERMANOVA)

- Developing and understanding the limitations of methods to compute the sample size (these methods are principal to derive the sample size in a clinical study, and as a result can have a huge impact in the derivation of significant results)

- Developing good practices for Experimental Designs.

- Using these developments in multi-omic research (genomics to metabolomics, metagenomics, epigenomics, data sets from past and future projects)

- Using these developments in other applications in which we have running projects, like ecology, vulcanology, networkmetrics or ancient DNA.

Research Area:

  • Information Science and Engineering (ENG)
  • Life Sciences (LIFE)

For a correct evaluation of your candidature, please send the documents below to Professor José Camacho Páez (

  • CV
  • Letter of recommendation (optional)