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The Genome Data Science lab, led by Full Professor Fran Supek at the Biotech Research & Innovation Centre (BRIC), University of Copenhagen, is launching the "A-SOuRCCE" project—AI for Single-cell Omics and Reproducible Cardiometabolic and Cancer Exploration. This initiative, supported by a 1.7M € grant from the Novo Nordisk Foundation, focuses on developing agentic AI systems to accelerate discoveries in genomics, particularly in cancer and cardiometabolic diseases. The project aims to integrate advanced AI agents with knowledge graphs to analyze large-scale single-cell RNA-seq and ATAC-seq datasets. The goal is to generate, prioritize, and validate mechanistic hypotheses about gene regulation in disease, leveraging population genetics (GWAS) data. This research sits at the intersection of computational biology, cancer genomics, and AI-driven bioinformatics, offering opportunities for PhD students and postdoctoral researchers interested in cutting-edge data science and biomedical research. The lab collaborates with leading institutions, including IRB Barcelona, Centre for Genomic Regulation (CRG), and Ruđer Bošković Institute. Prospective candidates should have a strong background in computational biology, bioinformatics, or related fields, and a keen interest in AI applications in genomics. Funding is secured for the project, ensuring a supportive research environment. Recruitment for PhD and postdoc positions will open soon. Interested applicants are encouraged to follow lab updates for application details.

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].