Postdoc Position – Multi-Modal AI: The University of Twente is inviting applications for a Postdoctoral position focused on developing and validating advanced AI models to enhance the early detection of liver cancer. This interdisciplinary role requires collaboration with experts in AI, medical imaging, and hepatology, aiming to improve clinical outcomes for patients with liver disease.
Postdoc Position – Multi-Modal AI for Early Detection of Liver Cancer
Designation
Postdoctoral Researcher
Table of Details
| Detail | Information |
|---|---|
| Research Area | Multi-Modal AI, Early Detection of Liver Cancer |
| Location | University of Twente, Enschede, Netherlands |
| Eligibility/Qualification | PhD in AI, Biomedical Engineering, or related field |
| Salary | €4,241 – €4,728 gross/month (depending on experience) |
| Duration | 3 years |
| Deadline for Application | October 6, 2025 |
Research Area
This position will focus on integrating medical imaging, multi-modal clinical, and omics data using explainable AI (XAI) approaches for predicting hepatocellular carcinoma (HCC).
Job Description
As a postdoctoral researcher, you will:
- Develop advanced AI models for early detection and risk prediction of liver cancer using longitudinal MRI data and multi-omics profiles.
- Collaborate closely with radiologists and hepatologists to align model development with clinical needs and priorities.
- Explore deep learning techniques, including convolutional and transformer-based architectures, for analyzing medical images.
- Implement explainable AI methods to connect imaging features with clinically relevant outcomes.
- Contribute to the creation of practical tools enhancing diagnostic and prognostic decision-making in liver disease.
How to Apply
Interested candidates should submit their applications online, including a CV, motivation letter, and list of publications. For more details, contact Dr. Maryam Amir Haeri at m.amirhaeri@utwente.nl.
Last Date for Application
October 6, 2025
Join us at the University of Twente to take part in cutting-edge research that bridges technology and healthcare, making significant contributions to the field of liver cancer detection and treatment.
