The Swiss Tropical and Public Health Institute (Swiss TPH) is a world leading institute in global health with a particular focus on low and middle income countries. Associated with the University of Basel, Swiss TPH combines research, education, and services at local, national, and international levels. 950 people from 95 nations work at Swiss TPH focusing on infectious and non communicable diseases, environment, society and health as well as health systems and interventions. The Department of Medical Parasitology and Infection Biology (MPI) investigates the biology and transmission of pathogens. Findings from this research inform the development of new diagnostics, treatments, and vaccines against malaria, tuberculosis, schistosomiasis, Chagas and other neglected tropical diseases. The Tuberculosis Ecology and Evolution Unit is part of the Medical Parasitology and Infection Biology Department at Swiss TPH. Led by Prof. Dr. Sebastien Gagneux, the Unit studies the causes and consequences of genetic diversity in the Mycobacterium tuberculosis complex (MTBC), the bacteria responsible for tuberculosis (TB). The research combines various disciplines to explore the global diversity of MTBC, the evolutionary forces driving this diversity, and the phenotypic consequences of this diversity for the biology and epidemiology of TB. The Unit also leverages cutting edge omics technologies to profile clinical MTBC isolates, with a strong emphasis on integrating genomics, proteomics, and other phenotypic data obtained experimentally and clinically through long term patient cohorts. Translational Data Scientist (80 100%) The Translational Data Scientist will play a key role in the research of the Tuberculosis Ecology and Evolution Unit. The candidate will contribute to multiple ongoing projects focused on understanding the genomic, phenotypic, and proteomic factors influencing the biology and epidemiology of TB. You will work closely with experimental and computational biologists to process and analyze large scale omics datasets, integrate multi omics data (such as genomics, proteomics, and clinical data), and interpret the resulting biological insights to advance TB research. Your various responsibilities include: Develop and customize computational workflows and algorithms to process and analyze raw data from sequencing based assays (e.g., whole genome sequencing, transcriptomics), proteomics (DDA, DIA, MRM), and phenotypic screens. Integrate and analyze multi omics data, including genomics, proteomics, and other experimental and clinical phenotypic data, to uncover insights into TB biology, evolution, and epidemiology. Contribute to the development and refinement of computational methods, such as proteogenomic modeling, GWAS, and pQTL analysis. Perform statistical analysis and visualization of large datasets to extract actionable biological insights. Work closely with experimental scientists to facilitate data interpretation and drive the development of re