The Infectious Disease Epidemiology (IDE) Laboratory offers an excellent interdisciplinary environment where experimentalists work closely with computational experts utilizing state-of-the-art genomic technologies. We ask fundamental questions on how bacterial phenotypes are determined by their genotypes in natural settings. We therefore utilize a broad range of high-throughput genomic and phenomic technologies to obtain whole genome sequencing of clinical and environmental bacterial strains and their key clinical phenotypes under various conditions. We then employ computational methods, in particular machine learning methods, to integrate the phenome and genome data with the goal of reconstructing the genotype-phenotype map and identifying robust causative and informative genomic biomarkers. The post-holder will conduct computational analysis of large-scale genomic collections and develop machine learning framework in collaboration with experimentalists and clinicians in the lab. We honestly think that asking deep questions in a team of different mindsets working together is a path towards fundamental understanding as well as enabling biomedical applications. We are embedded in BESE division (bese.kaust.edu.sa), which extends and supports a multi-disciplinary work environment. Furthermore, through the core laboratories (corelabs.kaust.edu.sa) we have access to the most recent equipment such as imaging, sequencing, and single-cell genomics. The IDE lab is part of the Smart Health Initiative (www.smarthealth.kaust.edu.sa), which aims at the development and usage of smart health technologies and knowledge to promote innovation that transforms healthcare delivery system of Saudi Arabia and the world from traditional medicine to precision medicine. Central to this initiative, is the collaboration between KAUST scientists with clinicians in the best in-Kingdom medical centres.