Researcher in Single-cell Data Science for Cancer Research

We are seeking a highly motivated data scientist or bioinformatician with experience in single-cell analysis to tackle one of the central challenges in breast cancer research: understanding and predicting endocrine treatment resistance directly from patient-derived single-cell data. The successful candidate will work at the interface of computational biology and clinical research, contributing to analyses that directly inform ongoing trials and future treatment strategies.

A two-year postdoc/researcher position (with possible 1-year extension) is available at the Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital. The position is part of a newly funded project supported by the Norwegian Cancer Society and the Norwegian Breast Cancer Society, focusing on molecular mechanisms of treatment resistance in estrogen receptor positive breast cancer.

This project aims to dissect how cancer cells adapt to endocrine therapy by integrating single-cell multiomic data with well-annotated clinical material. We analyze paired scRNA seq and scATAC seq data from local clinical trials, providing a unique opportunity to study treatment response directly in patient-derived samples.

A central objective is to reconstruct gene regulatory networks and enhancer driven transcriptional programs underlying resistance, with a particular focus on transcription factor activity, regulatory circuits, and epigenetic memory. The project aims to translate these discoveries into clinically relevant biomarkers using bulk RNA sequencing and DNA methylation data.

Oslo University Hospital is a workplace with great diversity. We believe this is crucial for solving our tasks in the best possible way. We want this diversity to be reflected among the applicants for our positions, and we encourage all qualified candidates, regardless of background, to apply!

Work tasks

Key responsibilities

• Analyze and integrate single-cell multiomic data including scRNA-seq and scATAC-seq across patients and timepoints
• Infer transcription factor activity, regulatory circuits, and enhancer driven programs
• Identify and characterize tumor subclones using copy number variation from single-cell data
• Link molecular features to treatment response and clinical outcomes
• Translate single-cell discoveries into biomarker models in bulk RNA sequencing and DNA methylation data
• Develop reproducible, scalable, and well-structured analysis workflows
• Lead and contribute to high quality scientific publications and presentations
• Use of AI based approaches, including agent-based workflows for data analysis, is encouraged

Qualifications

• PhD in bioinformatics, computational biology, systems biology, or a related field
• Experience with single-cell sequencing data analysis (e.g. 10x Genomics platforms)
• Strong programming skills in R and/or Python
• Experience with integrative analysis of multiomic data is an advantage
• Interest in cancer biology and translational research
• Strong written and verbal communication skills in English
• Experience with AI based analysis frameworks is considered a strength

We offer

• A highly collaborative and interdisciplinary research environment
• Access to unique clinical trial datasets and close integration with clinical partners
• Opportunities to work on biologically and clinically impactful questions
• Strong support for scientific development and career progression
• Competitive salary according to qualifications
• Possibility of prolonging the position