03/03/2020
Marie Skłodowska-Curie Actions

MSCA-IF: Joint application at the University of Granada. Department of Computer Science and Artificial Intelligence.

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  • OFFER DEADLINE
    01/07/2020 13:00 - Europe/Brussels
  • EU RESEARCH FRAMEWORK PROGRAMME
    H2020 / Marie Skłodowska-Curie Actions
  • LOCATION
    Spain, Granada
  • ORGANISATION/COMPANY
    International Research Projects Office
  • DEPARTMENT
    Promotion and Advisory Unit
  • LABORATORY
    NA

Professor Juan Manuel Fernández Luna, from the Department of Computer Science and Artificial Intelligence at the University of Granada, welcomes postdoctoral candidates interested in applying for a Marie Skłodowska-Curie Individual Fellowships (MSCA-IF) in 2020 at this University. Please note that applicants must comply with the Mobility Rule (more information: http://sl.ugr.es/0aNV).

Brief description of the institution:

The University of Granada (UGR), founded in 1531, is one of the largest and most important universities in Spain. The UGR has been awarded with the "Human Resources Excellence in Research (HRS4R)", which reflects the UGR’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 a leading institution in research, located in the top 5/10 of Spanish universities by a variety of ranking criteria, such as national R&D projects, fellowships awarded, publications, or international funding.

UGR is one of the few Spanish Universities listed in the Shanghai Top 500 ranking (http://sl.ugr.es/0aw0). The Academic Ranking of World Universities (ARWU) places the UGR in 268th position in the world and as the 4th 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 Documentation (ranked in the 36th in the world) or Food science technology (ranked 37th in the world), Mathematics and Computer Science (ranked among the top 76-100 in the world).

The UGR has 4 researchers at the top of the Highly Cited Researchers (HCR) list in the Computer Science area. With regard to broader subject fields, the UGR is ranked in 45th position in the universities worldwide in the discipline of Engineering. It is also well recognized for its web presence (http://sl.ugr.es/0a6i) taking 36th place in the top 200 Universities in Europe. Internationally, we bet decidedly by our 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 66 projects, with total funding of 18.02 million euros, and for H2020, 80 projects with total funding around 20.6 million euros.

Brief description of the Centre/Research Group

The candidate would be host at the Computer Science and Artificial Intelligence department at the University of Granada, although she/he will work very closely with members of the Department of Preventive Medicine and Public Health from this university. More specifically, in the context of the AIRES initiative, the postdoc researcher will work in a wider and multidisciplinary environment, where the members present experience of joint working in multicenter projects. Members have an individually and collectively distinctive track record(s) in computer sciences, systematic review, study quality assessment, meta-analysis, evidence grading, public health, cardiometabolic research, and various forms of evidence synthesis including both randomized and real-world data.

More specifically, the research group from the Professor Fernández Luna is basically focused on the intelligent access field, more specifically in the areas of Information Retrieval and Recommender Systems, where they have been working for more that 20 years and published a wide range of papers in the main international journals and conferences. Machine Learning and Text Mining have been the main tools used to solve the problems faced in these areas.

Project description

Published biomedical research needs to be synthesised for health practitioners. This currently takes too long to contemporaneously enhance health care quality because the methods of evidence synthesis that bring together published studies to underpin guidance for practice have well recognised, serious delays taking on average 5 staff members over 12 months to complete a review. We postulate that artificial intelligence (AI) can assist in evidence synthesis, improving the timeliness of guidelines. The objective of this project is, using beyond state-of-the-art methodology, develop an integrated system using modern AI technologies to support the complete process of systematic reviews. We will validate the performance the AI-based system quantifying its accuracy, precision, heterogeneity, bias and generalizability compared to a standard meta-analysis. We wish to form an international consortium of well-established researchers with individually distinctive track records in computer science, systematic review, study quality assessment, meta-analysis, evidence grading, public health, cardiometabolic research, and various forms of evidence synthesis including both randomized and real-world data. We will collaborate as a multidisciplinary team involving relevant stakeholders. This will allow the delivery of a much-needed, exciting, ground breaking, high-quality and impactful project. Our output will help accelerate the process of meta-analyses, evidence synthesis and transfer of research into guidelines for improving the quality of health care.

The postdoc researcher should be an expert in AI techniques, specifically in information retrieval and text mining. She/he will be in charge of proposing solutions and evaluating them for the automation of systematic reviews.

Research Area

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

For a correct evaluation of your candidature, please send the documents below to Professor Juan Manuel Fernández Luna (jmfluna@decsai.ugr.es):

  • CV
  • Letter of recommendation (optional)

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