Computational biology and Bioinformatics
Advanced computational methods to analyse our large collections of complex, biological data
The Nilsson lab has a long track-record of developing computational methods and tools to analyze genomics data. Including gene expression data (ref), network modeling (ref), DNA copy number data (ref), and massively parallel reporter assays(ref). We combine genome-wide association studies (GWAS) based on unique sample materials and large sets of phenotypes, including flow cytemetric and gene expression data as well as advanced imaging.
We are continously seeking talented and highly motivated postdocs, graduate students and master students within computational biology and bioinformatics. Please contact us for information on open positions or other available opportunities.