This project aims to identify occupational risk, by combining the power of historical records of the global population and the precision data of personalized occupational exposure records. The combination will be achieved through advanced machine learning and AI techniques. The project will be carried out by an interdisciplinary team of experts in biomedical data acquisition , advanced data processing, AI algorithms, epidemiology and clinical validation. The work of this consortium is perfectly aligned with the goals of DGS, regarding their objectives for the national plan of Occupational Health. It will explore the large datasets from the latter governmental agency, and will contribute to drafting better decision making tasks and public policies definition.