Postdoctoral Positions, Computational and Experimental Systems Immunology, University of Oslo


Two three-year Fellowship positions for a Postdoctoral research Fellow with background in either experimental or computational systems biology are available at the Department of Immunology (University of Oslo). The positions are available from January 2018 with a flexible start, ideally in the first quarter of 2018.

The positions are located in the research group of Associate Professor Victor Greiff, who will start his research group at the Department of Immunology, Institute of Clinical Medicine, in January 2018.

The focus of Dr. Greiff’s research group will lie on the quantitative understanding of immune repertoire diversity and specificity using high-throughput immunogenomics and immunoproteomics coupled to high-dimensional and high-performance computational biology and machine learning.

Job descriptions

Position 1: Development of single-cell antibody immunogenomics and immunoproteomics methods to enable the high-throughput investigation of the diversity and specificity of antibody repertoires.

Position 2: Development of bioinformatics, computational biology and machine learning approaches to preprocess, analyze and interpret large-scale immune repertoire data with application to in silico immunoprofiling and discovery of novel immunodiagnostics and immunotherapeutics.

The specific aims of each topic are flexible and will be developed jointly by the postdoctoral researcher and the PI.


For Position 1, a PhD in biology, immunology, molecular biology, experimental systems biology, or a related field is required. Broad knowledge and experience in immunological techniques including flow cytometry, ELISA, ELISPOT, functional assays, high-throughput sequencing. Experience in proteomics sample preparation technologies and a working knowledge of statistics and good computational skills (R, python) are considered strong advantages.
For Position 2, a PhD in a quantitative discipline is required (Bioinformatics, Computer Science, Statistics, Physics, Applied Mathematics, or a related field). Expertise in developing and maintaining code, handling large amounts of transcriptomics and proteomics data as well as expertise in high performance computing and machine learning is expected. Immunological knowledge is considered a strong advantage.

More information on the application process can be found here.