Bioinformatician
Solliciteren
Plaats
Leuven3000
Vlaams-Brabant
België
Contract
Vooltijds, Onbepaalde duurDatum gepubliceerd
2026-02-13Online to:
2026-04-14EUR 20.00 HOUR
Bioinformatician
- Panda Intelligence
- Vlaams-Brabant
- 4 dagen geleden
As a Senior / Principal Bioinformatician, you will lead hands-on analysis across spatial transcriptomics and single-cell omics to deliver clear, decision-ready insights for target discovery and validation. You'll help set the standard for reproducible analysis and scalable workflows in a discovery R&D environment.
Key responsibilities:
Own end-to-end analysis of spatial transcriptomics (including in situ approaches) and scRNA-seq
Integrate spatial/single-cell results with additional internal and external datasets to strengthen hypotheses
Drive target identification and prioritization (gene networks, pathways, candidate targets)
Build and maintain reproducible pipelines and scalable workflows (not one-off scripts)
Produce structured reporting and clear visualizations for scientific stakeholders
Maintain strong data practices: documentation, version control, and robust data organization
Essential Requirements
MSc or PhD in Bioinformatics, Computational Biology, Data Science (or similar)
5+ years experience in bioinformatics / computational biology (industry preferred)
Strong hands-on experience with single-cell and/or spatial transcriptomics
Advanced R and/or Python (clean, reusable code; workflow mindset)
Strong statistics foundation (QC, differential analysis, modelling)
Experience operating in cross-functional discovery teams and translating biology questions into analysis plans
Desirable Requirements
Multi-omics integration (e.g., proteomics, genetics) and/or digital pathology exposure
Workflow/infrastructure tooling (e.g., Nextflow, Docker, SQL, graph databases like Neo4j)
Machine Learning/Deep Learning exposure for omics or target discovery support.
Key responsibilities:
Own end-to-end analysis of spatial transcriptomics (including in situ approaches) and scRNA-seq
Integrate spatial/single-cell results with additional internal and external datasets to strengthen hypotheses
Drive target identification and prioritization (gene networks, pathways, candidate targets)
Build and maintain reproducible pipelines and scalable workflows (not one-off scripts)
Produce structured reporting and clear visualizations for scientific stakeholders
Maintain strong data practices: documentation, version control, and robust data organization
Essential Requirements
MSc or PhD in Bioinformatics, Computational Biology, Data Science (or similar)
5+ years experience in bioinformatics / computational biology (industry preferred)
Strong hands-on experience with single-cell and/or spatial transcriptomics
Advanced R and/or Python (clean, reusable code; workflow mindset)
Strong statistics foundation (QC, differential analysis, modelling)
Experience operating in cross-functional discovery teams and translating biology questions into analysis plans
Desirable Requirements
Multi-omics integration (e.g., proteomics, genetics) and/or digital pathology exposure
Workflow/infrastructure tooling (e.g., Nextflow, Docker, SQL, graph databases like Neo4j)
Machine Learning/Deep Learning exposure for omics or target discovery support.