Scientists from Erasmus MC University Medical Centre Rotterdam and Delft University of Technology have joined forces to work towards improved care of patients with knee osteoarthritis. Using state-of-the-art artificial intelligence techniques, the researchers will develop advanced computer algorithms for clinical decision support. These algorithms construct a detailed, personal profile of each individual patient, based on clinical measures, imaging (radiography & MRI), and genetic risk. The resulting patient profile will aid the clinician in diagnosing the disease in its early stage, estimate the risk of disease progression, and predict the effects of potential treatments. Besides contributing to better treatment of osteoarthritis, the developed technology will be applicable to many other diseases as well.
This project aims at enabling earlier diagnosis of osteoarthritis (OA), improving prediction of OA progression and effects of interventions, and enhancing the understanding of underlying disease processes, using a comprehensive imaging-genetics approach. The project involves two postdocs working closely together on the integration of genomics and imaging data and calls for expertise in building complex (deep) learning models on such data and development of novel statistical learning methodology to derive powerful diagnostic, predictive and causal models.
This Erasmus MC – TU Delft Convergence project brings together worldwide experts in early diagnosis of OA, genomics of OA, as well as advanced mathematical modelling and image analysis. This expertise in combination with unique resources (the world largest longitudinal dataset on OA, and clinical trials through the OA-trial bank) creates an enormous opportunity to advance the field.
Qualification and skills for both postdocs:
- PhD degree in Computer Science, Mathematics, Physics, Electrical Engineering, Biomedical Engineering, or a related field.
- Experience with machine learning techniques, causal inference, osteoarthritis research, biomedical image analysis and/or genetics/bioinformatics is an advantage.
- Familiar with programming (preferably Python).
- Strong mathematical skills and affinity with experimental work are required, the same goes for a desire to bridge the gap between research and practice.
The postdocs should have a deep interest in the convergence of health sciences, physical sciences, and engineering to foster individual health and keep the healthcare system sustainable. They will work closely with the supervisors, Principal investigators and Collaborating investigators of the project to conduct high calibre research. They are also encouraged to initiate and lead collaborative work with other postdocs within the Convergence for health(care) initiative. Salary will be commensurate with qualification and experience.
About this position
Recruitment takes place until the vacancy is filled.
Hours a week: 36
Dr. ir. Stefan Klein
Prof. Marco Loog
Deep Imaging - Genetics for Osteoarthritis