PhD fellowship in AI for Cancer Genomics

at  KU SCIENCE BIO BRIC

OUR GROUP AND RESEARCH

The Supek group is an interdisciplinary team, working at the intersection of genomics, molecular biology, and artificial intelligence. The lab performs statistical analysis of large-scale datasets (cancer genomics, population genomics) using cutting-edge techniques including artificial intelligence (e.g. DNA and protein language models). We further generate our own genomics data by DNA/RNA sequencing (particularly by Oxford Nanopore), and gene editing to generate models of cancer evolution (e.g. CRISPR/Cas12a system for combinatorial gene disruption).
In our research, we focus in frontier research projects e.g. recently finished ERC project “HYPER-INSIGHT”, and ongoing ERC “ STRUCTOMATIC: Mutational processes and impact of structural variants in somatic cells ”. Furthermore, we are embedded in a broad network of international collaborators (see e.g. EU Horizon consortia “DECIDER” and “LUCIA”, where we study ovarian cancer and lung cancer genomics, respectively).
The Supek group fosters a dynamic and inclusive atmosphere, where excitement about science is valued. We are highly committed to mentoring and career development of PhD students, postdoctoral fellows, and other team members. We are looking for enthusiastic, driven lab members to join us in our mission in pushing the boundaries of human knowledge, and fighting cancer with genomics .
The lab is at the Biotech Research & Innovation Centre, a flagship Danish biomedical research institute, and a part of the University of Copenhagen, the top-3 ranked university in continental Europe in the latest Shanghai Rankings. More information about the group is given on the lab website https://www.genomedatalab.org/

PROJECT DESCRIPTION

We invite brilliant minds in computational biology to join us at the cutting-edge of cancer genomics research, harnessing the power of artificial intelligence and evolutionary modeling. As part of our innovative team, you’ll be at the forefront of identifying non-coding driver mutations in cancer genomes, a challenge that has long puzzled traditional analysis methods.
Our AI-DRIVERS project aims to understand of cancer evolution by developing and applying state-of-the-art AI models to predict the functional impact of non-coding mutations. Your work will innovate by combining these AI predictions with novel evolutionary frameworks, allowing us to infer selection on regulatory elements and identify new cancer drivers hidden in the ‘dark matter’ of the genome.
You’ll work with extensive whole-genome sequencing datasets from various cancer types, applying and refining AI models to predict changes in gene regulation. Your research will involve developing new methodologies to account for heterogeneous mutation rates across the genome, a critical step in accurately detecting selection in non-coding regions.
This project offers a unique opportunity to bridge computational genomics, artificial intelligence, and cancer biology. You’ll be applying cutting-edge deep learning architectures, including convolutional networks and transformers, to genomic data. Additionally, you’ll have the chance to collaborate with experimental biologists to validate your computational predictions using CRISPR-based approaches.
Your PhD work will employ a powerful combination of AI, evolutionary modeling, and large-scale genomic analysis. The results of your studies will be pivotal in uncovering new diagnostic markers, potential therapeutic targets, and fundamental insights into cancer genome evolution. Join us in this exciting endeavor to unlock the secrets of non-coding cancer drivers and pave the way for new approaches in personalized cancer medicine.

JOB DESCRIPTION

Your key tasks as a PhD student at SUND are:

• Carrying through an independent research project under supervision.
• Completing PhD courses or other equivalent education corresponding to approximately 30 ECTS points.
• Participating in active research environments including a stay at another research team.
• Obtaining experience with teaching or other types of dissemination related to your PhD project
• Teaching and disseminating your knowledge.
• Writing a PhD thesis on the grounds of your project

• Carrying through an independent research project under supervision.
• Completing PhD courses or other equivalent education corresponding to approximately 30 ECTS points.
• Participating in active research environments including a stay at another research team.
• Obtaining experience with teaching or other types of dissemination related to your PhD project
• Teaching and disseminating your knowledge.
• Writing a PhD thesis on the grounds of your projec