Ayudas a Equipos de Investigación Científica Biomédica - BBVA Foundation
Internal closing date in IRBLleida: Friday, November 22nd, 2019.
Funding agency: Fundación BBVA
The Grant Call has the objective of achieve the commitment of Fundación BBVA with the promotion of scientific research and its projection to society, as the way to increase the individual and collective opportunities and face the main challenges of the century XXI in an efficient approach.
In the Biomedicine area, there will be awarded a maximum of 5 grants, with a maximum budget of 125.000 € each. The maximum length of the project will be of 3 years. The grants will award research projects highly innovative in any of the next transversal areas:
- Metabolism and disease. The effects of metabolism in the disease include cellular processes as cell aging, signaling and gene regulation, apoptosis and fat metabolism, which is associated to prevalent diseases as metabolic syndrome and tumorous processes. The applicant projects must imply a significant progress in the knowledge of the cellular metabolism alterations linked to the disease development. It will allows a progress in its approach, understanding and diagnosis.
- Molecular imaging. This grant is focused in the promotion of the development of new approaches on molecular imaging which, in combination with biochemistry and cell biology techniques, will develop new diagnosis and therapeutic-diagnostic applications. The objective of the projects applying in this call must develop imaging markers for the in vivo characterization of elements, at molecular and cellular level in normal and pathologic conditions to improve the knowledge of potential biochemical and physiological abnormalities. It would be used to give access to new markers for early markers of the disease.
In the Big Data area, there will be awarded a maximum of 5 grants, with a maximum budget of 100.000 € each. The grants will award basic or applied research projects for big and complex data analysis, including algorithms and techniques of machine learning, classification and regression trees, linear models for wide data, random forest and boosting, support vector machines, kernel methods and pattern recognition o data visualization. The maximum length of the project will be of 2 years.
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