Through advances in artificial intelligence (AI), medical imaging has gained an increasingly important role in precision medicine. AI methods are being used both in radiology (“radiomics”) and pathology (“pathomics”) to develop prediction models that are at the basis of more precise and personalized clinical decision making. While radiomics and pathomics models often have similar goals and contain complementary information, these research fields are largely separated. Moreover, despite major advancements in these fields, implementation in real-world clinical practice remains limited.

To address this, the aim of the AI for Integrated Diagnostics (AIID) research line is to join forces of radiomics and pathomics to create trustworthy models to aid clinicians in decision making. Our mission is to develop multi-modal machine learning methods primarily for improved diagnosis and therapy response in oncology. While we focus on radiology and pathology, our vision is to extend our methods to additional datatypes. By smartly combining the different datatypes through AI, our methods could substantially impact clinical practice. The current project funded by a Dutch National Growth Fund AINed Fellowship kickstarts this research line with three PhD students and two Postdocs.

This PostDoc focusses on developing novel multi-modal deep learning methods. Only a handful of studies in recent years have just scratched the surface of “RadioPathomics” (i.e., combined radiomics and pathomics). You will develop multi-modal machine learning methods that simultaneously learn from both modalities by sharing representations of the different modalities during learning, e.g., through coordination (promoting equivalence) or co-learning (sharing and aligning intermediate representations). These should be model- and disease-agnostic, so you can incorporate the developments from our radiomics and pathomics research, and apply your methods to different disease domains.

You should be an independent and highly motivated researcher.

• You have a PhD degree in the fields of medical image analysis and/or machine learning.
• You should be able to communicate and work with researchers from various fields. Excellent proficiency in English is required.

• You will receive a temporary position for 1-3 years at Erasmus MC.
• The gross monthly salary amounts a minimum of € 3.359,- and a maximum of € 5.292,- (scale 10), depending on your level of education and relevant experience, based on a full-time working week of 36 hours.
• Excellent fringe benefits, such as a 13th month that is already paid out in November and an individual travel expense package.
• Pension insurance with ABP. We take care of approximately 2/3 of the monthly contribution.
• An International Office which aids you in preparing for your arrival and stay.

Erasmus MC

The research will be conducted at the Biomedical Imaging Group Rotterdam (BIGR), which is part of the department of Radiology & Nuclear Medicine, and the PHANTOM group, which is part of the department of Pathology, both of the Erasmus MC, University Medical Center Rotterdam. The department of Radiology & Nuclear Medicine is one of the largest imaging departments in Europe with 10 clinical MRI scanners at several field strengths. The department of Pathology conducts thorough analysis of diverse clinical, sequencing, and pathology imaging data, examining tissue samples from various tumors (e.g., tongue, breast, lung, liver, skin, eye, bladder, colorectal) using staining techniques like H&E, IHC, and IF. Both departments have an international and diverse character with a good balance between internationally recognised, high-end research and an excellent social working environment.

You will collaborate with a team of experienced researchers with backgrounds in image analysis, machine learning, radiology, pathology, surgery, and oncology. As part of the project you will also work with worldwide renowned experts in soft-tissue cancer within our sarcoma artificial intelligence (SAI) consortium.

The supervision for the projects will be provided by associate professor Stefan Klein, PhD, and assistant professor Martijn Starmans, PhD. You will act as co-supervisor of the PhD students as well.