PhD Machine Learning for Medical Video Analysis in Cancer Treatment

The advances of fluorescent markers provide powerful new possibilities for guided precision medicine in cancer surgery. However, fluorescent signals in soft tissue can be difficult to interpret, especially when they are weak, unstable, or partially obscured during minimally invasive procedures. To help surgeons achieve the best possible post-operative quality of life for cancer patients, we are looking for a highly motivated PhD candidate to join an international research effort combining medical imaging, computer vision, and artificial intelligence.

What are you going to do?

In this four-year PhD project, you will develop real-time machine-learning systems for the analysis of fluorescence-guided endoscopic videos. Your primary goal is to design and evaluate machine learning and deep learning algorithms capable of reliably detecting weak fluorescence signals injected into soft tissues to mark tumors and lymph nodes.

You will work on:

•         Developing an automated system for fluorescence video analysis
•         Integrating the developed algorithms into a real-time prototype system
•         Collaborating with surgeons and industrial partners to understand clinical requirements and refine system functionality
•         Participating actively in consortium meetings and interdisciplinary collaboration with academic, clinical, and industrial partners 

Employed PhD candidates are expected to spend 10% of their working hours on teaching and/or supervising candidates.

You are an enthusiastic and curious researcher with:

•         A Master’s degree in Computer Science, Artificial Intelligence, Biomedical Engineering, Applied Mathematics, or a related field
•         Strong programming skills
•         Experience with machine learning and deep learning frameworks (e.g., PyTorch)
•         Interest in medical imaging, computer vision, or video analysis
•         Excellent written and spoken English communication skills
•         Motivation to work in an interdisciplinary, international environment

• 232 vacation hours per year, based on a 38-hour workweek (1.0 FTE). You can also work more or fewer hours in exchange for more or fewer free hours. For example, with a 40-hour workweek, you save 96 extra free hours, and with a 36-hour workweek, you lose 96 hours.
• End-of-year bonus of 8.3% and 8% holiday allowance.
• Extensive opportunities for personal and professional development.

The Faculty of Science and Engineering (FSE) provides teaching and research across a wide range of disciplines, from physics and biology to artificial intelligence, mechanical engineering, and pharmacy. In close collaboration with partners from industry, healthcare, and society, we contribute to the urgent challenges of our time, such as energy, sustainability, digitization, and medical technology. Our community is open and informal, with more than 7,000 students, 1,000 PhD students, and 1,400 staff members from all over the world. If you would like to learn more about the Faculty of Science and Engineering, visit rug.nl/fse. 

This PhD position is part of the Interreg PRECISE project, a large cross-border European research initiative focused on innovations for precision cancer surgery. You will join a vibrant and international research environment at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, within the Faculty of Science and Engineering, University of Groningen. The candidate will become a member of the Intelligent Systems Group of the Computer Science Department and will work under the supervision of Dr. Jiapan Guo (j.guo@rug.nl).

Do you have any questions or need more information?

Questions about the content of the job?
Jiapan Guo (Assistant Professor): j.guo@rug.nl

Questions about your application process?
Femke Postma (Human Resources Adviser): femke.postma@rug.nl