The successful candidate will be part of the EU funded ERC Advanced Grant ‘From GWAS to Function (GWAS2FUNC)’, and will focus on developing novel statistical genetic tools using GWAS data, that can be used for optimizing e.g. risk prediction, improving current genetic models or understanding biology. The candidate will work in an enthusiastic team of PhD students and postdocs, with diverse backgrounds, including statistics, bioinformatics, artificial intelligence, neuroscience, psychology and stem cell biology.
We are seeking a highly motivated, talented individual. You are required to handle large genetic and genomic datasets, with information on brain-related traits (e.g. cognition, schizophrenia, autism, mental retardation, neurodegenerative disorders), and subsequent bioinformatics annotation. The successful candidate needs to be proficient in statistics and statistical programming, and practical experience in the analysis of genomics data (e.g. expression data, GWAS, WGS, WES).
Your duties
- develop novel statistical tools for analyzing genome wide data, e.g. including
GxE, risk prediction and multivariate genetic analyses
- co-supervision of MSc and PhD students
- authoring and co-authoring manuscripts submitted to high quality journals
- some support (10% of time) with teaching is expected
- frequently present work at international community (at conference calls, or
conferences)