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Vlaams Instituut voor Biotechnologie (VIB) in Belgium seeks a bioinformatics technician to analyze single-cell and spatial datasets with a focus on in vivo perturbational data. You will develop and adapt computational pipelines and collaborate across computational and experimental teams to ensure robust analyses.
The role offers a flexible 80% (part-time) appointment with a competitive pay scale, health insurance, and access to a stimulating international research environment conducted mainly in
The Laboratory of Causal Systems Immunology combines large-scale in vivo perturbation experiments, advanced mouse models of immune diseases and causal learning to uncover how genes shape immune-cell states and predict how the immune system responds to interventions. This tight integration of experimental immunology with data-driven experiments allows us to tackle fundamental biological questions with direct biomedical relevance. We are embedded in both the VIB-UGent Center for Inflammation Research, a leading center unravelling the cellular and molecular mechanisms of inflammatory diseases, and the VIB Center for AI & Computational Biology, a young, ambitious center whose research groups address biological questions through the lens of AI.
We have developed, and continue to advance, a set of untargeted and targeted spatial, single-cell, single-nucleus, and perturbational omics technologies. Our in vivosingle-cell CRISPR technologies allow us to screen for dozens of molecular factors in vivo during development and disease. These technologies transform the speed, scale and resolution at which in vivoimmune-cell pathways can be unraveled. By combining these approaches with single-nucleus ATAC-seq and spatial data, we are moving towards a comprehensive understanding of the regulatory mechanisms that shape liver cell states in health and disease, including metabolism, cancer, regeneration and development.
In this role, you will apply innovative computational approaches to analyze a broad range of single-cell and single-nucleus datasets, including RNA-seq, ATAC-seq and perturbational omics. You will also work with spatial transcriptomics data, using technologies such as MERFISH/MERSCOPE, Visium HD and ATERA. Depending on your interests and strengths, you can choose to focus more strongly on either single-cell and perturbational data analysis or spatial data analysis, while also gaining exposure to the broader range of technologies. If you have a particular interest or stronger experience in one of these areas, we would be very interested to hear about it.
Your work will involve developing, adapting and fine-tuning computational pipelines, often building on approaches developed within our lab or institute. You will work closely with both computational and experimental colleagues to analyze data in a detailed and scientifically sound manner, integrate and compare results across different data types and projects, and uncover biological patterns and insights. Strong collaboration and communication across the computational and experimental sides of the lab will be an important part of the role.
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