Postdoctoral positions: data integration of omics data for personalized health in Zürich

Our groups are tightly embedded in the Swiss initiatives on personalized health promoted by the and networks. Our major task is to contribute an in-depth molecular analysis of samples from patients to support therapeutic decisions and the discovery of novel targets. These activities are carried under the umbrella of the Swiss Multi-Omics Center (), which also unites the expert on clinical genomics of the Health2030 Genome Centre in Geneva. of the molecular basis of methylmalonic aciduria in infants provides a representative example of the studies we perform.

With the great progress made in recent years in the digitization of clinical samples by mass spectrometry, the challenge shifted from data generation to data interpretation. More efforts are needed to translate data into information and insights that are actionable. To work on these challenges, we are seeking two candidates that will pioneer reusable workflows for the analysis, integration, and visualization of molecular data. You are expected to build on domain knowledge and create pipelines that simplify data interrogation by non-experts or clinicians. As a member of our team, you will be working in a highly collaborative environment and be involved in national and international networks for precision medicine. You will be expected to work side-by-side with wet-bench scientists and assist in delivering data analyses that fill the gap between data and information and support clinical decisions with deep molecular evidence.
 

You are expected to:

• Design and implement reusable analysis and visualization workflows for large scale clinical omics data, with a focus on proteomics and/or metabolomics data.
• Collaborate with the members of the in Zurich and Geneva on the analysis of multi-omics data, and with specialists of the .
• Interface with clinicians at the data analysis stage.

Essential qualifications:

• PhD in biological sciences with a strong focus on proteomics or metabolomics data analysis.
• Must be well versed with various programming languages, and have a passion for the design and implementation of effective UI.
• Proficiency in written and verbal English communication.
• Positive attitude toward collaborative work and learning of novel technologies.
• Experience in any of the following fields is also highly desirable: multi-omics data integration, containerization technologies, Unix/Linux, data driven analysis, statistics, machine learning, data visualization. 

ETH Zurich is a family-friendly employer with excellent working conditions. You can look forward to an exciting working environment, cultural diversity and attractive offers and benefits.