PhD student machine learning of gene isoform variants in immune cells

Working Environment

You will be based in the Department of Genetics at the University Medical Center Groningen (UMCG) and the Faculty of Medical Sciences at the University of Groningen. The University of Groningen is a globally oriented research university ranked among the world’s top 100. The Faculty of Medical Sciences is the second oldest medical faculty in the Netherlands.
Our Functional Genomics group, supervised by Prof. Dr. Lude Franke, is part of the Genetics department and includes 15 researchers focused on understanding disease through genetic and genomic data. The broader department consists of approximately 400 staff involved in research, diagnostics, and patient care. We value open science and active participation in major international consortia such as eQTLGen and sc-eQTLGen.

Job description

Gene splicing can generate multiple transcripts (isoforms) from a single gene, potentially influencing disease mechanisms. However, for many genes, the full repertoire of isoforms is still unknown and therefore knowledge on the impact of isoforms for rare diseases in clinical settings is limited. With the development of long-read sequencing technologies, reliable identification and quantification of these transcripts is now possible. We are seeking a motivated postdoctoral researcher to investigate and predict the relationship between gene isoforms and (rare) disease.
Job description
As a PhD student, you will:
- Study the effect of (rare) genetic variants on isoform expression using long-read single-cell expression data from immune cells (blood and gut).
- Develop and apply computational methods to improve isoform quantification in short-read data, leveraging long-read data as a reference.
- Employ AI-based models to analyze genetic effects on isoform expression and apply these to predict effects in rare disease cases
- Present your findings in scientific publications and at (inter)national meetings.
You will study the impact of (rare) genetic variants on isoform expression within patient cohorts. You will work with unique datasets available through the single-cell eQTLGen consortium and will benefit from international collaborations within this network.

Requirements

You have:
- A (soon to be completed) MSc degree in bioinformatics, statistical genetics, computer science, artificial intelligence, molecular biology, or a related field;
- Strong communication skills and proficiency in English;
- Motivation for collaborative work and a proactive approach;
- Fundamental programming skills (e.g., Python, R, Java, Bash);
- Interest or experience in AI/machine learning and data analysis;
- Affinity with statistics or willingness to learn;
- Experience with single-cell data, long-read sequencing, or genetics is a plus but not required.

Conditions of employment

- A fully funded, 4-year PhD position at the UMCG.
- A starting salary of € 3.109,- gross per month in the first year, increasing up to € 3.939,- gross per month in the fourth year (PhD scale, as of 1 July 2025)
- 8% holiday allowance and 8.3% year-end bonus
- The conditions of employment comply with the Collective Labour Agreement for Medical Centres (CAO-UMC).
- Access to world-class genomic datasets and high-performance computing infrastructure
- Supervision by an experienced, internationally recognized research team
- Extensive opportunities for training, attending conferences, and international collaborations
- A stimulating, collegial and inclusive research environment
- Excellent career prospects: our PhD graduates often continue in academia, industry, or data-driven research roles
Intended starting date: April 1st 2026 or upon agreement.
For questions about the position
Do you have questions about this position or are you unsure if your profile matches? Please contact Dr. Marc Jan Bonder ([email protected]). We look forward to your application!
Link
Research.rug Marc Jan Bonder

Additional information

For more information about this vacancy you may contact:
Marc Jan Bonder (+31)06 4140 1972
[email protected] Lude Franke (+31) 06 4154 9962
[email protected]

Applying for a job

Solliciteren

Please use the the digital application form at the bottom of this page - only these will be processed. You can apply until 23 February 2026. Within half an hour after sending the digital application form you will receive an email- confirmation with further information.
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