Translational Data Scientist (80 – 100%)

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 reproducible analysis pipelines and help train/supervise BSc, MSc and PhD students.Ensure reproducibility, quality control, and hygiene of data, code, and project documentation following FAIR principles.Communicate research findings through reports, presentations, and peer-reviewed publications.You should have the following experience and skills:PhD in bioinformatics, computational biology, systems biology, or a related field and a minimum of 5 years of postdoctoral or equivalent professional experience.A strong publication record in the relevant field, with a demonstrated ability to publish research in high-impact journals.Proficiency in programming and scripting with R and Python as well as strong knowledge of Linux/Unix environments, including experience in data processing on HPC clusters, data mining, algorithm development, and statistical modeling with experience in methods such as Bayesian statistics, Markov models, and machine learning.Demonstrated ability to develop and maintain computational workflows for genomics, proteomics (DDA, DIA, MRM), and other omics data types, and proficiency in integrating and visualizing such multimodal data.Solid foundation in genetics, with experience in GWAS, pQTL, and integrative analyses such as proteogenomic modeling.Expertise in Protein-Protein Interaction (PPI) and Protein-Protein Association (PPA) networks, including analysis of dysregulation and the application of statistical methods to interpret PPI/PPA data.Background in TB research, with an understanding of MTBC biology, phylogenetic diversity, and epidemiology.What we offer:Meaningful work in an international environment.A state-of-the-art workplace in our new building with its own canteen on the dynamic BaseLink site in Allschwil.Interesting encounters with people from a wide variety of backgrounds.Being part of a committed and motivated team with short information and decision paths.Attractive employment conditions, versatile further education opportunities, and mentoring.Job conditions:Start Date: 1 March 2025 (or based on agreement).Duration: 2 years (with possible extension).Percentage: 80-100%.Internal job title: Scientific Collaborator II.In their native language, Swiss TPH employees talk about what motivates them in their daily work.How to apply:Please submit your application online.CV.Motivational letter including names and contact information (email or phone number) of 1 – 2 references.Reference letters and diploma.Swiss TPH strives to create an inclusive environment that welcomes and values diversity in all its forms, including gender, race, ethnicity, disability, sexual orientation, and socio-economic background. We are committed to ensuring equal opportunities for everyone, and we actively work to eliminate barriers to underrepresented groups in global health leadership. Together, we can make the world a healthier place. We look forward to receiving your application.Please note that we can only accept applications via our online recruiting tool. As long as the position is online on our company website, we are open for new applications. Applications via email or external recruiter will not be considered.Contact: #J-18808-Ljbffr