Predictive Medicine and Translational Research of Respiratory, Cardiovascular and Metabolic Diseases

The Group of Predictive Biomedicine and Translational Research of Respiratory, Cardiovascular and Metabolic Diseases is a multidisciplinary group of researchers from different departments and health sciences areas and institutions, mainly from the School of Medicine of the Complutense University of Madrid (UCM), Spain. The UCM group has been positively evaluated by the National Quality Assessment and Accreditation Agency of Spain (ANEC). The group is composed by biologists, geneticists, medical doctors, surgeons, physics, statisticians and nutritionists.<br /><br />The group is involved in different research lines as studies related to predictive medicine, molecular mechanisms involved in Covid-19 mediated cell damage, in cellullar and molecular mechanisms associated with thrombo-coagulation and in the development of algorithms by AI to predict obesity based on life style and genetics etc. We use clinical data, molecular biology and genetic in addition to cells cultures. We have published more than 250 scientific papers and we have directed more than 80 thesis. <br /><br />Our PI, Professor Antonio López Farré, was awarded the National Prize on Research as Young Researcher of the Decade of Spain in 2001 awarded by the Royal National Academy of Medicine of Spain (RANM). In 2019, he was awarded the Annual Prize from the RANM and named academician and also received the Gold Cross of Honour of Health of the Community of Madrid, the highest award.

Research lines<br /><br />1. Study genes and genetic polymorphisms related to nutrition and physical exercise. <br />2. Identify biomarkers related to the prediction of respiratory, cardiovascular, metabolic, and cancer diseases. <br />3. Identify biomarkers and molecular signalling pathways related to the pharmacological response in cardiovascular-related cells <br />4. Molecular mechanisms estimulated or inhibited by Covid-19 in cultured endothelial cells. <br />5. Carry on scientific algorithms using several types of machinelearning (decisión trees, Deep-learning) to identify persons at risk to develop overweight/obesity and its comorbidities (cardiovacular diseases, cancer, respiratory diseases, diabetes mellitus type, etc) <br /><br />Some research topics linked to the research lines<br /><br />1. Development of algorithms using artificial intelligence based on genetic and protein biomarkers to predict overweight/obesity and their comorbidities. <br />2. Search for new biomarkers and their interactions that predict developed outcome of different diseases. <br />3. Look for new mechanisms by which Covid-19 proteins damage different types of endothelial cells. <br />4. Study of molecular mechanisms associated with the development and progression of abdominal aortic aneurysms and the effects of new drugs. <br />5. Analysis of the mechanisms associated with thrombocoagulation and with different inhibitory drugs.

The following documents are to be submitted by the candidate:<br />" Curriculum Vitae<br />" Motivation letter<br />" Recommendation letters from previous research centres<br />" Demonstrative research and lab experience (publications, books, participation in research projects, research techniques, technical skills, etc.)