PhD Position in 3D Deep Learning for Dental Diagnostics

This PhD position at the Medical University of Vienna focuses on advancing 3D deep learning techniques for dental diagnostics. The project, part of the FFG BRIDGE initiative ARTIS, aims to extract diagnostic insights from high-resolution 3D intraoral scans of teeth and gums, which are routinely captured during dental visits but currently underutilized. The successful candidate will design and implement deep learning models, starting from point cloud architectures like PointNet++ and DGCNN, and extend them to graph neural networks for mesh-based analysis. The work will involve collaboration with dentists for model validation and presentation of results at international conferences. The position is based within the University Clinic of Dentistry and offers a multidisciplinary environment combining machine learning and clinical dentistry.

• Develop deep learning models for analyzing 3D intraoral scans, starting with point cloud architectures like PointNet++ and DGCNN.
• Extend models to graph neural networks to process mesh structures of dental scans.
• Implement explainability methods to identify key geometric features influencing diagnostic predictions.
• Collaborate with dentists to validate models and ensure clinical relevance of results.
• Present research findings at international conferences and publish in peer-reviewed journals.