Postdoctoral Studies in Bioinformatics and Translational Breast Cancer, Karolinska Institutet (KI), Sweden

Summary

The research group of Professor Johan Hartman at the Department of Oncology-Pathology (OnkPat), Karolinska Institutet, is seeking a highly motivated postdoctoral researcher with a strong background in bioinformatic data analysis. The project focuses on clinical and translational breast cancer research, precision cancer medicine, tumor heterogeneity, and tumor-stromal interactions using genomic, transcriptomic, single-cell, and spatial omics data integrated with machine learning approaches.

Postdoctoral Studies in Bioinformatics and Translational Breast Cancer

Key Position Details

Research Area

• Primary Fields: Bioinformatics, Computational Biology, Translational Breast Cancer Research, Precision Oncology, and Cancer Genomics.
• Key Methodologies: Multi-omics integration, spatial transcriptomics, single-cell RNA sequencing, biostatistics, AI-assisted molecular pathology, and population registry analysis.

Location

Department of Oncology-Pathology, Karolinska Institutet, located mainly at BioClinicum in Solna, Sweden (with collaborative ties to KTH and the Science for Life Laboratory / SciLifeLab).

Eligibility & Qualifications

General Scholarship Eligibility

• Open to foreign researchers (researchers residing outside Sweden intending to conduct postdoctoral research at KI). Persons residing in Sweden or having received their academic education at KI/Swedish institutions are not eligible for this scholarship scheme.
• Applicants must hold a doctorate (Ph.D.) or equivalent foreign degree, or have completed all degree requirements prior to the intended start date.
• The scholarship can be granted for a maximum of 2 years within a 4-year window following doctoral degree completion.

Essential Requirements

• Ph.D. degree in Bioinformatics, Computational Biology, Molecular Biology, Computer Science, or an equivalent quantitative field.
• Programming & Environment: High proficiency in scripting languages (such as R or Python) and comfortable working in a Linux command-line environment.
• Data Experience: Demonstrated experience analyzing next-generation sequencing data (DNA, RNA, DNA methylation) supported by peer-reviewed publications.
• Domain Knowledge: Solid foundational understanding of molecular biology and cancer biology.
• Communication & Organization: Excellent written and oral English communication skills, with strong data management and documentation practices.

Desirable Competencies

• Proven experience in biostatistics and analyzing clinical cohort data (prospective/retrospective).
• Familiarity with single-cell sequencing, spatial transcriptomics, multi-omics integration, or computational pathology tools.
• Experience utilizing public cancer genomics databases (e.g., TCGA, COSMIC, dbSNP).
• Hands-on experience with relevant AI/machine learning software applied to oncology.

Job Description & Responsibilities

• Perform multi-omics analysis of genomic, transcriptomic, and DNA methylation datasets (including somatic mutation calling, copy-number alterations, gene expression profiling, and pathway/signature analyses).
• Develop, optimize, and maintain computational pipelines for high-throughput sequencing, single-cell, and spatial omics data.
• Apply machine learning and biostatistical methods to integrate multi-omics profiles with large-scale clinical registries and patient cohort datasets.
• Collaborate closely with a multidisciplinary team composed of clinicians, bioinformaticians, data scientists, and cancer biologists.

How to Apply

Applications must be submitted electronically through the Varbi recruitment portal.

Required Documents (in English or Swedish):

1. Curriculum Vitae (CV): Including defense date of Ph.D. thesis, thesis title, previous and current academic positions, titles, distinctions, and committee service.
2. Complete Publication List.
3. Summary of Current Work: Brief research summary (maximum 1 page).

• Application Portal: Apply via KI Varbi Portal
• Contact Persons:
  • Johan Hartman: johan.hartman@ki.se
  • Xinsong Chen: xinsong.chen@ki.se

Last Date for Application

September 22, 2026

Link