Time-to-Event Modeling in Critical Care and Veterinary Medicine
Job description
ABOUT GHENT UNIVERSITY
Ghent University is a world of its own. Employing more than 15.000 people, it is actively involved in education and research, management and administration, as well as technical and social service provision on a daily basis. It is one of the largest, most exciting employers in the area and offers great career opportunities.
With its 11 faculties and more than 85 departments offering state-of-the-art study programmes grounded in research in a wide range of academic fields, Ghent University is a logical choice for its staff and students.
For the faculty of Engineering and Architecture, research group IDLab, we are looking for a m/f/x interested in doctoral research on time-to-event modeling in critical care and veterinary medicine.
YOUR JOB
We are seeking a highly motivated and talented PhD candidate to work at the intersection of statistical survival analysis, machine learning, uncertainty quantification, and causal inference, with applications in human intensive care (ICU) and chronic kidney disease (CKD) in cats. The research aims to design robust, interpretable, and clinically actionable models for time-to-event prediction, capable of dealing with heterogeneous and longitudinal data, while providing calibrated uncertainty estimates and causal insights.
Key Research Topics within this doctoral research project are:
Job profile
WHAT WE CAN OFFER YOU
How to apply
Send your CV, copy of your diploma and grades (if already in your possession) and a motivation letter to Sofie.V...@UGent.be using “Time-to-Event PhD” as mail subject. Deadline September 21st, 2025.
For more information about this vacancy, please contact prof. Sofie Van Hoecke (Sofie.V...@UGent.be) or prof. Luc Duchateau (Luc.Du...@UGent.be).
Best regards,
Sofie
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prof. Sofie Van Hoecke, MSc, PhD
Ghent University - imec | AATower | Tech Lane Ghent Science Park 122 | B-9052 Zwijnaarde
Dept. of Electronics and Information Systems | IDLab | Data Science Lab | PreDiCT team