The Translational Immunology Laboratory managed by Dr. Adrian Liston is looking for a skilled and motivated bioinformatician. This internationally recognized research group is embedded in the infrastructure of the VIB and KUL and consists of three major research divisions: the tissue and disease team, the molecular Treg team and the primary immunodeficiency team that unite to understand the factors that influence immune activation and immune tolerance.
The bioinformatician will work closely with all teams to manage and support all next generation sequencing approaches.
Main duties and responsibilities
Develop and use novel computational pipelines for analysis of complex human and rodent research data. The successful candidate will be responsible for design and computational support of NGS experiments, especially RNA-seq, and the construction analytical strategies for interpreting and visualizing multimodalities of large omics datasets. In particular, the successful candidate will develop and maintain computational pipeline for analysis of single cell transcriptome sequencing.
Excellent communicator with proven ability to work in a collaborative environment. Efficient multitasker that collaborates easily but can work independently. Strong interest in innovative approaches to keep pipelines and technology at cutting edge. Capacity to work at the interface with biologists and clinicians.
- MSc (plus experience) or PhD degree in appropriate scientific or technical discipline (preferably bioinformatics/computational genomics or biology, with formal understanding of basic biological processes);
- Strong programming skills capable of constructing, maintaining and optimizing computational pipelines for analysis of large datasets, particularly single cell RNA-seq. Experience with NGS platforms (including Illumina) and single cell analysis (transcriptome/genome) is highly desirable;
- High throughput computing experience in Unix environments with working knowledge of programming languages such as Java, C/C++, perl and python;
- Experience with retrieving, normalizing and analyzing high-throughput datasets using R packages/Bioconductor, as well as in the visual presentation of biological data from high-throughput experiments;
- Knowledge in statistics applied to NGS data analysis is desirable;
- Fluency in written and spoken English is required;
- Experience in immunology is a plus, but is not required.