Fran Supek
1 month ago
PhD Fellowship in AI for Single-Cell Disease Genomics at University of Copenhagen University of Copenhagen in Denmark
Degree Level
PhD
Field of study
Cell Biology
Funding
The position is a full-time, fixed-term PhD fellowship for 3 years, conditional on enrolment in the UCPH Graduate School. The fellowship offers a competitive salary of approximately 31,242 DKK per month (about 4,182 EUR) plus pension. Employment includes social benefits and integration into an international research environment. The position is funded by the NNF-funded A-SOuRCCE project.
Deadline
Expired
Country
Denmark
University
University of Copenhagen

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Where to contact
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About this position
The University of Copenhagen’s Biotech Research & Innovation Centre (BRIC) is offering a PhD fellowship in AI for Single-Cell Disease Genomics, supervised by Professor Fran Supek. This position is part of the NNF-funded A-SOuRCCE project, which aims to develop autonomous AI 'co-pilots' using Large Language Models (LLMs) to analyze complex single-cell datasets, discover regulatory circuits, and generate hypotheses for disease mechanisms, with a particular focus on cancer genomics and cardiometabolic diseases.
The research will involve developing standardized analysis workflows for scRNA-seq and scATAC-seq datasets, curating and processing large public single-cell datasets, and applying AI frameworks to infer gene regulatory circuits and validate AI reasoning. The project is highly interdisciplinary, integrating genomics, molecular biology, and artificial intelligence, and offers the opportunity to work with a dynamic team of postdocs, students, and software engineers. The Supek group is embedded in a vibrant international research environment and collaborates with leading consortia such as ERC, Danish Cancer Society, and EU Horizon projects.
Applicants should have a master’s degree (or equivalent) in bioinformatics, computational biology, data science, molecular biology, physics, or computer science. Strong programming skills in Python and/or R are required, and familiarity with workflow systems (Nextflow, Snakemake) or machine learning frameworks (PyTorch) is desirable. Experience with omics data analysis, especially single-cell RNA-seq/ATAC-seq, and knowledge of cancer biology, somatic evolution, or tumor heterogeneity are advantageous. Excellent English language skills, motivation, curiosity, and the ability to work both independently and collaboratively are essential. The master’s degree must be equivalent to a Danish master’s degree (two years).
The fellowship is a full-time, fixed-term position for 3 years, conditional on enrolment in the UCPH Graduate School. The salary is competitive, starting at approximately 31,242 DKK per month (about 4,182 EUR) plus pension. The position includes social benefits and integration into an international research environment in Copenhagen, one of the world’s most livable cities. The application deadline is 10 February 2026, with interviews expected in March 2026. The start date is 1 May 2026 or soon thereafter, with flexibility.
To apply, submit your application electronically via the University of Copenhagen job portal, including a motivated letter of application, CV, certified copy of your Master’s degree and transcript, and a publication list. For further information, visit the lab website or contact Professor Fran Supek at [email protected].
Funding details
The position is a full-time, fixed-term PhD fellowship for 3 years, conditional on enrolment in the UCPH Graduate School. The fellowship offers a competitive salary of approximately 31,242 DKK per month (about 4,182 EUR) plus pension. Employment includes social benefits and integration into an international research environment. The position is funded by the NNF-funded A-SOuRCCE project.
What's required
Applicants must hold a master’s degree (or equivalent) in bioinformatics, computational biology, data science, molecular biology, physics, or computer science. Strong programming skills in Python and/or R are required. Familiarity with workflow systems (Nextflow, Snakemake) or machine learning frameworks (PyTorch) is desirable. Experience with omics data analysis, preferably single-cell RNA-seq/ATAC-seq, and knowledge of cancer biology, somatic evolution, or tumor heterogeneity are considered a plus. Applicants should demonstrate motivation, curiosity, ability to work independently and in a team, and excellent English language skills. The master’s degree must be equivalent to a Danish master’s degree (two years).
How to apply
Submit your application electronically via the University of Copenhagen job portal. Include a motivated letter of application, CV, certified copy of your Master’s degree and transcript, and a publication list. Ensure all documents are in PDF format and submitted before the deadline.
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