PhD student machine learning of gene isoform variants in immune cells

As a PhD student machine learning of gene isoform variants in immune cells, you will work on understanding how gene splicing generates multiple transcripts (isoforms) from a single gene and how these isoforms may influence (rare) 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. In this project, you will investigate and predict the relationship between gene isoforms and (rare) disease using advanced computational and AI-based approaches.

Closing date: February 23

About the project

Gene splicing can generate multiple transcripts (isoforms) from a single gene, potentially influencing disease mechanisms. With long-read sequencing technologies, reliable identification and quantification of transcripts is now possible. You will study the impact of (rare) genetic variants on isoform expression within patient cohorts, using long-read single-cell expression data from immune cells (blood and gut). You will work with unique datasets available through the single-cell eQTLGen consortium and will benefit from international collaborations within this network.

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.

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.

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 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.

What do we offer

• A fully funded, 4-year PhD position at the UMCG.
• 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.
• 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.