\\n PhD in statistical genetics

Employer

University of Lausanne (UNIL)

Work Location

Lausanne, Switzerland

Employment fraction

100%

Type of contract

temporary

Job tasks

The Statistical Genetics Group of Zolt\\xc3\\xa1n Kutalik at Unisant\\xc3\\xa9 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

• the estimation of (inverted U-shaped) non-linear omics-disease causal effects;
• detecting such signatures from e/p/mQTL effect size vs minor allele frequency relationship genome-wide;
• 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).

Profile requirements

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).

How to apply

If you are interested in this challenging and highly interesting position, please visit the following link where you will find more information about the job and how to apply :\\n \\n \\n \\n \\n \\n

\\n\\n Swiss Institute for Bioinformatics\\n \\n\\n

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