Summary
Inria Saclay-Île-de-France is offering a PhD scholarship focusing on developing robust few-shot learning techniques for CT imaging using multimodal clinical data. The successful candidate will contribute to groundbreaking research that harnesses artificial intelligence to enhance diagnostic capabilities in medical imaging.
PhD Position in Robust Few-Shot Learning for Foundational Model in CT Imaging, Gif sur Yvette, France
Designation
PhD Candidate
| Detail | Information |
|---|---|
| Research Center | Inria Saclay-Île-de-France |
| Contract Type | Fixed-term contract |
| Duration | 3 years |
| Remuneration | 2300€ gross/month |
| Starting Date | Flexible, starting from 1st October 2026 |
| Location | Gif sur Yvette, France |
Research Area
- Optimization, Machine Learning, Statistical Methods
- Big Data and Medical Imaging
Eligibility/Qualification
- Master’s degree or Engineering degree in a relevant field
- Strong background in AI, mathematics, optimization, and statistics
- Experience with Python programming; familiarity with PyTorch or TensorFlow is highly recommended.
- Fluency in English and/or French
Job Description
The PhD candidate will:
- Develop new few-shot learning techniques for CT image classification.
- Create models for few-shot tumor segmentation
- Analyze robustness and generalization capabilities of models.
- Validate findings on public datasets and the EDS-APHP dataset.
Main Activities:
- Programming in Python/PyTorch
- Conducting bibliographical studies
- Designing and testing deep learning architectures
- Performing mathematical optimization and convergence analysis
- Writing scientific reports
How to Apply
Interested candidates should submit a CV and a motivation letter through the Inria website. Applications sent from other channels are not guaranteed processing.
Last Date to Apply
August 31, 2026
Contact Information
- PhD Supervisor: Emilie Chouzenoux
- Email: emilie.chouzenoux@inria.fr
Join us in this innovative research environment and contribute to the advancement of medical imaging technology!
