Postdoctoral Position in Multi-omics and AI: Applications are invited for a Postdoctoral Researcher position at the Science for Life Laboratory (SciLifeLab), Stockholm, Sweden. The position focuses on developing advanced AI-driven gene regulatory network (GRN) inference methods using spatial and single-cell multi-omics data combined with gene perturbation approaches.
The project is supervised by Professor Erik Sonnhammer and is embedded within a strong interdisciplinary research environment involving Stockholm University, KTH Royal Institute of Technology, and Karolinska Institutet.
Postdoctoral Position in Gene Regulatory Network Inference Using Spatial & Single-Cell Multi-omics and AI
Summary Table
| Item | Details |
|---|---|
| Position | Postdoctoral Researcher |
| Research Focus | GRN inference, AI, spatial & single-cell multi-omics |
| Institution | Science for Life Laboratory (SciLifeLab) |
| Location | Stockholm, Sweden |
| Supervisor | Prof. Erik Sonnhammer |
| Required Degree | PhD (Bioinformatics / Molecular Biology / related) |
| Key Skills | Python, R, Matlab, AI/ML, Multi-omics |
| Application Mode | |
| Deadline | Not specified |
Designation
Postdoctoral Researcher (Postdoc)
Research Area
- Gene Regulatory Network (GRN) inference
- Spatial transcriptomics and single-cell multi-omics
- Artificial Intelligence and deep learning
- Gene perturbation analysis
- Cancer systems biology (with focus on liver cancer)
Location
Science for Life Laboratory (SciLifeLab), Stockholm, Sweden
SciLifeLab is a national center for large-scale life science research and a joint initiative of:
- Stockholm University
- KTH Royal Institute of Technology
- Karolinska Institutet
Eligibility / Qualification
Candidates must meet one of the following criteria:
- PhD in Bioinformatics or a closely related field, with:
- Strong knowledge of molecular biology
- Proven experience in multi-omics data analysis
OR
- PhD in Molecular Biology (or related field)plus:
- At least 2 years of postdoctoral experience in bioinformatics research and programming
- Documented scientific publications
Essential Skills
- Proficiency in sequence and gene expression data analysis
- Strong programming skills in Python, R, and/or Matlab
- Experience with AI / deep learning methods
- Working knowledge of UNIX/Linux environments
Job Description
The postdoctoral researcher will:
- Develop novel AI-based deep learning frameworks for GRN inference
- Integrate gene perturbation data with spatial and single-cell multi-omics datasets
- Design systems to infer perturbation designs from gene expression and chromatin accessibility data
- Construct region-specific GRNs linked to tissue phenotypes (e.g., cancer stages)
- Apply methods to spatial liver cancer datasets generated within the group
- Perform programming, data analysis, benchmarking, and computational modeling
- Contribute to understanding cancer dysregulation, with long-term relevance to therapeutic development
How to Apply
Interested candidates should contact the supervisor directly for further information and application details:
📧 Email: Erik.Sonnhammer@scilifelab.se
🌐 Lab Website: http://sonnhammer.org/
Applicants are encouraged to include:
- CV
- Brief cover letter describing research interests
- List of publications
Last Date for Apply
March 16, 2026
