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Postdoctoral Position in Computational Biology and Metabolomics

SIB - Swiss Institute of Bioinformatics

Lausanne, Switzerland

Job tasks

The Computational Biology Group develops and applies methods for the integrative analysis of largescale biological and clinical data. This includes molecular phenotypes like gene-expression and metabolomics data, as well as organismal phenotypes (ranging from patient data to growth assays). We focus particularly on relating these phenotypes to genotypes such as "Single Nucleotide Polymorphisms" (SNPs) and "Copy Number Variants" (CNVs). Our goal is to move towards predictive models in order to improve the diagnosis, prevention and treatment of disease. A complementary direction of research pertains to relatively small genetic networks, whose components are well known. We collaborate closely with experts of the field to identify biological systems that can be modeled quantitatively. Our group is embedded within the Department of Computational Biology of the University of Lausanne and a member of the Swiss Institute of Bioinformatics.

We are looking for an outstanding candidate for a postdoctoral researcher position in our group. Work will focus on the design, development, and application of computational approaches to analyze large-scale data from human cohorts. Specifically, we are interested in studying untargeted metabolomics data in order to identify potential new disease markers and mechanisms through integration with genotypic and other phenotypic data. The appointee will develop her research projects while working in an interdisciplinary and highly collaborative team including computer scientists, physicists, and molecular biologists.

Profile requirements

A Ph.D. in computer science, statistics, physics or related fields is preferred, but applicants with a Ph.D. in Life Sciences are also welcomed to apply, provided they can demonstrate previous experience in computational biology and/or analysis of large-scale data. Knowledge in metabolomics, programming and statistics is an advantage.

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