Research Infrastructure Specialist in Computational Biology/Bioinformatics (CRISPR Functional Genomics)
Do you want to contribute to top quality medical research?
Computational methods and AI applied to large-scale molecular data are transforming biology – from molecular structures and cellular processes to human health and ecosystems. As part of SciLifeLab, a unique nation-wide infrastructure and research community that combines advanced life science technologies with data and AI expertise, the CRISPR Functional Genomics unit at Karolinska Institutet is looking for a Research Infrastructure Specialist in Computational Biology and/or Bioinformatics.
Your mission
You will build and maintain reproducible pipelines for in-depth analysis of high-throughput CRISPR gene-perturbation data. You will support CFG and its users in data analysis, management, and delivery. You will have the opportunity to contribute to multi-modal data integration to shape how high-dimensional omics data are transformed into actionable biological insights. Together with CFG’s wet-lab scientists and our user community, you will help drive a new era of quantitative and predictive biology.
More specifically, you will engage in the following areas:
- Analysis, visualization, and interpretation of NGS-based perturbation datasets with existing and emerging methods
- Support of CFG users in all aspects of data analysis and data handling
- Application and development of robust statistical approaches for hit calling and data interpretation
- Management of datasets for FAIR compliance and AI/ML-based discovery
- Contribute to multi-modal data integration
Eligibility requirements
- PhD in Computational Biology, Bioinformatics, Systems Biology, or a related field
- Proven methodological and research expertise
- Strong programming skills (Python, R, Bash or similar) for omics data processing, QC, statistical testing, and visualization to support biological discovery
- Proficiency in working with Unix/Linux environments
- Solid foundation in statistical and quantitative methods
- Strong communication skills and a collaborative, service-minded approach
- Fluency in English, spoken and written
For employment as Research Infrastructure Specialist at Karolinska Institutet, the eligibility requirements stated in the Guidelines for non-teaching positions at Karolinska Institutet are applied in relation to the established profile of employment.
To be eligible for an employment as Research Infrastructure Specialist the applicant must have demonstrated research expertise and been awarded a PhD or a qualification from a foreign higher education institution deemed equivalent to a Swedish PhD. The applicant must also have demonstrated technological and methodological expertise.
Assessment criteria
Experience or expertise in any of the following areas will be considered meritable:
- NGS and Omics Data Analysis: Processing and visualization of large-scale sequencing data (FASTQ/BAM, alignment, QC, variant calling)
- Single-cell and spatial omics workflows.
- CRISPR/Mutagenesis Screen Analysis: High-throughput screen analysis, including UMI handling and hit calling (e.g., MAGeCK, Bagel).
- Pathway and Gene Set Analysis: Gene set enrichment and pathway analysis using fgsea, clusterProfiler, Enrichr, ReactomePA, and databases such as KEGG, Reactome, and GO.
- Pipeline Development: Development and maintenance of reproducible pipelines (Snakemake, Nextflow) with version control and containerization (Docker/Singularity).
- Multi-Modal Data Integration: Combining CRISPR or mutagenesis data with complementary data types (transcriptomics, proteomics, imaging).
- AI/ML Applications: Applying machine learning or AI to predict gene function or discover functional relationships from perturbation data.
- FAIR & Metadata Management: Knowledge of public repositories, metadata standards, and ensuring datasets are FAIR and AI-ready.
After an overall assessment of the expertise and merits of the applicants in relation to the subject area, Karolinska Institutet will determine which of them has the best potential to contribute to a positive development of the activities at KI.