PhD Student Position in Bioinformatics and Data-Driven Life Sciences at Stockholm University

Stockholm University is inviting applications for a PhD student position in Bioinformatics, with research focused on data-driven life sciences and gene regulatory network inference using multi-omics data. The project, based at the Department of Biochemistry and Biophysics and affiliated with SciLifeLab, aims to develop novel AI and deep learning techniques to enhance gene regulatory network analysis, leveraging gene perturbation designs for single-cell and spatial omics data. The research will contribute to understanding cell type and tissue heterogeneity, with applications in areas such as cancer development. Applicants should have a strong background in bioinformatics, computational biology, or a related field, with specific coursework in Chemistry, Molecular Biology, Biotechnology, Computer Science, Mathematics, or Physics. Essential skills include proficiency in Python, Matlab, R, UNIX, and experience with omics data analysis. Familiarity with deep learning frameworks such as PyTorch or TensorFlow is highly desirable. Candidates must demonstrate strong analytical thinking, creativity, collaboration, and independence, as well as proficiency in written and spoken English. The position is a fixed-term, full-time doctoral employment for up to four years, with a fixed salary. The role may include up to 20% work in teaching, research, or administration. The application deadline is 22 February 2026. Interested candidates should apply via the Stockholm University recruitment portal, submitting a personal letter, CV, and all required documents as specified in the application instructions. For more information, contact Professor Erik Sonnhammer or Professor Andreas Barth. Stockholm University is committed to equal opportunities and a discrimination-free workplace. The research environment is highly collaborative, with access to advanced technical resources and expertise through SciLifeLab, a national center for molecular biosciences.