Data Science Internship: Panoramic Tooth Mapping

Philips is a 100% health technology company with Data and AI being an integral part of its strategy. This internship explores the reconstruction of panoramic 3D dental scenes from sparse intraoral images using self-supervised learning. By leveraging masked autoencoders and NeRF-inspired architectures, the goal is to learn implicit representations of the full oral cavity from limited visual input. These approaches will enable the generation of simulations and synthetic data of cameras moving in the mouth, which can be exploited for improving and training other related AI models.

Your role:

• Conduct a review of image-based 3D reconstruction, mapping, and self-supervised methods.
• Develop a data strategy on which input dataset to use or create.
• Implement various self-supervised and mapping methods.
• Benchmark the reconstruction and mapping results.
• Generate synthetic scanning path and data and evaluate its quality.
• Document the results in a technical report.

You're the right fit if:

• Currently studying towards your Master WO (MSc.) in Data Science, Mathematics, Applied Mathematics, Computer Science, Physics, Electrical/Electronic/Biomedical engineering.
• Experience with Python programming is essential.
• Good knowledge of machine learning practices in PyTorch.
• Passion for 2D/3D rendering and mapping.
• Experience with state-of-the-art AI models in computer vision.
• Language: good written and spoken English.
• Previous internship experience is not necessary but a plus.
• Good communication skills and enthusiasm to work in an international team.

How we work together
We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week.

About Philips
We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others.