Summary
The University of Oslo (UiO) invites applications for a PhD Research Fellow position in bioinformatics and computational biology at the Department of Clinical Molecular Biology (EpiGen), Campus Ahus. This position is funded by the Research Council of Norway and offers an exciting opportunity to join an interdisciplinary team developing biophysically interpretable machine learning models for identifying functional long-range gene regulatory interactions in cancer. The fellowship period is three years, free of teaching obligations, and the successful candidate will contribute to a PhD thesis submitted to the University of Oslo.
Designation
PhD Research Fellow
Research Area
- Bioinformatics
- Computational Biology
- Molecular Biology
- Human Genetics/Genomics
- Data Mining
- Machine Learning
- Computational Programming
- Network analysis in 3D genome regulation
- Non-coding mutations in cancer genome
- Integrated multi-omics data analysis (especially single-cell experiments)
Location
Department of Clinical Molecular Biology (EpiGen), University of Oslo, Ahus Campus, 1748 Lørenskog, Norway.
Eligibility/Qualification
Required Qualifications:
- Admission to a PhD program at the University of Oslo, or a binding agreement for admission.
- A five-year Master’s degree or equivalent studies recognized by the faculty.
- Master’s degree in bioinformatics or computational biology. Applicants with an MSc in physics, computer science, applied mathematics, or statistics are also encouraged if they demonstrate strong interest and aptitude for molecular biology and human genetics.
- Documented knowledge of statistical theory and methods, data mining, and machine learning methods.
- Documented shell script, R, Python, and C programming skills.
- Documented experience in big data analysis.
- Documented experience in high-throughput sequencing data analysis.
- Good written and oral English proficiency.
Grade Requirements:
- Average grade point for Bachelor’s degree courses: C or better (Norwegian educational system).
- Average grade point for Master’s degree courses: B or better (Norwegian educational system).
- Master’s thesis grade: B or better (Norwegian educational system).
Personal Qualities:
- Academic and personal ability to finish tasks on time.
- Ability to work independently or collaboratively in an interdisciplinary team.
- Self-motivated to learn, adaptable to new tasks, and interested in solving challenging scientific problems.
- Good communication skills and openness to new perspectives.
Desired Qualifications:
- Experience with ChIP-seq, ATAC-seq/scATAC-seq, RNA-seq/scRNA-seq, WGS, WGBS, or Hi-C data analysis.
- Experience in computational genome studies (e.g., TF-DNA interactions, gene networks, DNA mutations, and histone modifications).
- Experience with integrated multi-omics data analysis.
Job Description
The successful candidate will join an interdisciplinary team to develop novel computational methods and tools for predicting functional non-coding mutations in the cancer genome. This involves integrating diverse biological data, including transcription factor (TF)–DNA interactions, epigenetic features, and 3D genome organization, to identify functional long-range gene regulatory interactions. A particular focus will be on integrating multi-omics data from single-cell experiments to enhance predictive accuracy and biological interpretability.
The PhD research fellow will primarily focus on developing data mining methods, such as network analysis in 3D genome regulation, to integrate various biological information and identify functional non-coding mutations and their targets in long-distance regions. Predictions will be validated using both in vivo and in vitro experimental data in cancer. There may be an opportunity for a 3–6 month research visit to an international collaborator’s laboratory in the United States for advanced training.
How to Apply
Applications must be submitted via the recruitment system Jobbnorge by clicking "Apply for this job".
Your application should include:
- Application cover letter (statement of motivation and research interests).
- CV (summarizing education, positions, and academic work/scientific publications), entered directly into Jobbnorge’s CV form.
- A copy of the Master’s thesis, and a list of publications and academic works (maximum 5) for consideration.
- Certified copies of original Bachelor and Master’s degree diplomas and transcripts of records.
- Documentation of English proficiency, if applicable.
- Contact information for at least 3 references (name, relation to the candidate, institutional email address, and telephone number).
Applicants are asked to retrieve education results from Vitnemålsportalen.no. If not available, upload copies of transcripts or grades. All documentation must be in English or a Scandinavian language.
Last Date for Apply
October 21st, 2026
