Join our team within the ERC Consolidator Grant CARAVEL, a cutting-edge project focused on developing next-generation tools for extracting, modeling, and analyzing the brain vessel tree to study neurovascular aging. We seek a highly motivated PhD candidate to contribute to creating a novel framework for segmenting vessels from diverse neurovascular imaging modalities.
This PhD project aims to revolutionize vessel segmentation by creating a single, robust model capable of handling multiple imaging modalities and resolutions while accurately segmenting both arteries and veins. Current approaches rely on modality-specific models, limiting their versatility. This project seeks to overcome this limitation by developing a modality-agnostic framework capable of extracting the brain vessel tree while ensuring vessel continuity at the smallest scales.
Key Responsibilities
- Develop a novel framework for segmenting vessels from different neurovascular imaging modalities and sequences.
- Design a single model capable of handling any modality at any resolution to segment arteries or veins.
- Ensure topological preservation guarantees in the developed segmentation.
- Implement quality control mechanisms to flag potential errors in the segmentation.
- Contribute to the dissemination of research findings through publications and presentations.
- Contribute to the animation of research activities by actively participating in the group’s weekly meetings
- Contribute to teaching activities through lab assistance and marking
About the team
The successful candidate will be hosted within the AI4Health@EURECOM research group led by Prof. Maria A. Zuluaga. Prof. Zuluaga holds an ERC Consolidator Grant, providing access to cutting-edge research infrastructure and fostering a vibrant and competitive research environment. The candidate will benefit from such a dynamic and collaborative research environment. CARAVEL fosters strong interdisciplinary collaborations, providing opportunities to interact with researchers from diverse backgrounds, including national (Grenoble Institute of Neurosciences) and international (King’s College London) institutions, as well as clinical institutes (CHU Nice and Guy and St Thomas Hospitals).
Requirements
- Master's degree in Computer Science, Physics, Biomedical Engineering, or a related field.
- Proficiency in deep learning techniques and their application to image segmentation.
- Strong programming skills in Python (or similar languages).
- Experience with computer vision and algorithm development.
- Background in medical image analysis and processing is a plus
- Ability to work independently and as part of a collaborative research team.
- Strong problem-solving and analytical skills.
- Good command of English for reading/writing scientific articles and delivering oral presentations
Application
The application must include:
- Detailed curriculum vitae,
- A cover letter stating your motivation and fit for this project
- Name and address of two references.
- List of publications, if available
Applications should be submitted by e-mail to secretariat@eurecom.fr with the reference:
DS/MAZ/CARAVEL1/032025 before May 15th 2025.
Start date: September 1st 2025
Duration: Duration of the thesis
