Position opening: Post-doc fellow at the University of Nantes, France.
The University of Nantes (RMeS lab.) welcomes applications for a one-year post-doctoral position on teeth detection using Deep Learning.
Context of the Project:
The “Odon” project is a joint project between the University of Nantes and the Artefakt-AI company, we aim at developing tools for automatic detection of teeth and dental cares based on panoramic X-ray images. The “Odon” project is funded by the I-Site NExT initiative at the University of Nantes.
The final objective of the project is to propose means to automatically generate the patient’s odontogram based on panoramic X-rays. The odontogram is a schematic representation of the patient’s set of teeth. It shows all the present/absent teeth, along with every dental care the patient underwent. This diagram is being used not only for regular patient follow-up but may also be required for post-mortem identification.
In the framework of this study, we will propose a teeth segmentation method using Neural Networks, we will moreover assign to each detected tooth its anatomical label, and finally develop image analysis tools to recognize all possible dental cares the patient endured. The anatomical labeling will be dealt with via either the use of an appropriate neural network architecture, or via a clustering analysis. As for the recognition of dental treatments, image analysis & mathematical morphology will be exploited on top of the Deep Learning tooth detection step.
Thus, dental crowns, amalgams, dental fillings, root treatments, bridges and implants should be recognized and labeled so as to produce the odontogram.
In the framework of this study, we are looking for a highly motivated post-doc fellow who will propose innovative methods for teeth segmentation and dental treatments recognition.
The applicants should have:
-A PhD degree in computer science, Artificial Intelligence, Machine Learning, or Medical Image Analysis.
-A proven experience in Computer vision, image processing/analysis.
-Prior experience in Machine Learning applied to image segmentation.
-A strong publication record in any of the above-mentioned fields.
-A solid knowledge on algorithms and programming (Python, PyTorch, Keras, TensorFlow,... knowledge of C++/Java would be a plus).
-Language skills: Fluent verbal and written in English is required.
-Experience working with medical images is a plus.
One-year full time position, starting as soon as possible. The monthly net salary will be in between 2 000 and 2 400 euros (net income) depending on the candidate’s background and qualifications.
Applicants should submit a CV, including contact details of at least three referees along with a cover letter and a transcript of university results.
Applications should be sent to:
(c) GdR 720 ISIS - CNRS - 2011-2020.