This doctoral project aims to improve early detection and risk stratification of biliary tract cancers (BTC) in primary sclerosing cholangitis (PSC) patients by combining artificial intelligence with large-scale clinical, imaging, and omics data.
The PhD student will:
- Develop and apply AI-based models to identify PSC patients at risk of BTC using longitudinal clinical and MRI data.
- Integrate multi-omics and radiomics to identify molecular PSC subtypes associated with BTC risk.
- Explore genetic and epigenetic alterations to discover novel biomarkers for BTC risk prediction.
The student will be trained in advanced data analysis, AI and bioinformatics, as well as clinical interpretation of findings in collaboration with hepatologists and molecular scientists. The project is based on well-characterized national cohorts (SUPRIM and PiSCATIN) and existing biobank material, ensuring strong feasibility and translational relevance.
Application Deadline: December 26, 2025