Doctoral position in Statistical Genetics
Background: The Statistical Genetics Group of Zoltán Kutalik at Unisanté and the Department of Computational Biology at the University of Lausanne is investigating the interplay and the genetic architecture of complex human traits and diseases. In particular, we develop robust causal inference methods tailored to discover links between risk factors and complex diseases. We are doing so by jointly modelling the genetic architecture and the complex causal network of human traits. Additional research interests include: investigating gene-environment interactions, causal impact of molecular phenotypes (methylome, transcriptome, proteome, metabolome), copy-number variant associations etc. Via longstanding collaborations, we are fortunate to have access to several large cohorts (including the UK Biobank) with various omics data (eQTL-Gen, GoDMC). We have an extensive web of collaborations both in Switzerland (UNIL, CHUV, EPFL) and abroad (University of Bristol, University of Exeter, University of Groningen, University of Tartu, IST Vienna, University of Szeged, etc.). Our group is also member of the Swiss Institute of Bioinformatics.
The project aims to triangulate evidence for stabilising selection acting on transcript/protein/metabolite levels via (a) the estimation of (inverted U-shaped) non-linear omics-disease causal effects; (b) detecting such signatures from e/p/mQTL effect size vs minor allele frequency relationship genome-wide; (c) modelling evolutionary processes from cross-species transcript/protein/metabolite data. The candidate will be combining molecular association results with genetic and complex traits from the UK Biobank. The position is funded by the Swiss National Science Foundation (FNS).
Prerequisites: We are interested in recruiting talented and highly motivated individuals with an academic degree (MSc) in statistics / mathematics / bioinformatics / computer science. The ideal candidate should have
- strong background in statistics with keen interest for applications
- good programming skills (R, Python preferred, C++ is a plus)
- past experience with solving biological problems (especially experience with genome-wide association studies) using computational tools
- good communication skills and excellent command of English (French is a plus)
- MSc degree (statistics / mathematics / bioinformatics / computer science or equivalent).
Tasks: The candidate will spend at least 75% of her/his activity on personal scientific research and will be responsible for/participate in
- developing novel methodologies and their software implementation
- collaborate with other international teams
- performing GWAS / Mendelian Randomisation studies
Starting date: 1 Jan 2024
Duration: 4 years
Contact: Zoltán Kutalik (email@example.com; 021 692 39 16)