Université Côte d'Azur
Just Landed
New Today
PhD in AI and Medical Ultrasound: Differentiable Domain Randomisation for Robust Ultrasound Foundation Models Inria Université Côte d’Azur in France
Degree Level
PhD
Field of study
Computer Science
Funding
The position is a funded three-year PhD with an Inria PhD salary of approximately €2,300 gross per month. Funded research visits to MIT may be available through the project collaborations.
Country
France
University
Université Côte d'Azur
Apply for this position
Keywords
Suggested positions
About this position
PhD opportunity in AI and medical ultrasound focused on SynthUS, a project developing robust ultrasound foundation models through differentiable domain randomisation.
The research addresses the substantial variability of real-world medical ultrasound images, which presents a major challenge for AI-based analysis. The project will combine physics-based image simulation, generative AI, and differentiable learning to create models that generalise across imaging domains.
The PhD researcher will investigate image generation using learning-based and physics-based models, domain randomisation for learning domain-agnostic representations, differentiable ultrasound simulation for optimising synthetic training data, and foundation models for ultrasound segmentation.
The student will join the Epione team at Inria Université Côte d’Azur in Sophia Antipolis and work at the intersection of machine learning, medical imaging, and physics-based modelling. The project includes international collaborations with Professor Polina Golland at MIT and Dr. Reuben Dorent of Inria ARAMIS, with opportunities for research visits to MIT. Benjamin Billot and Nicholas Ayache are identified as the PhD supervisors.
The project offers an interdisciplinary research environment centred on AI-driven medical image analysis and the development of methods for robust ultrasound understanding.
Funding details
The position is a funded three-year PhD with an Inria PhD salary of approximately €2,300 gross per month. Funded research visits to MIT may be available through the project collaborations.
What's required
Applicants should hold a master’s degree in AI, computer vision, or biomedical engineering; have a strong background in deep learning with experience in medical imaging; possess advanced Python programming skills with experience in PyTorch and TensorFlow; demonstrate good scientific writing and communication skills; and have an interest in interdisciplinary research.
How to apply
Send a CV and a cover letter explaining your motivations to the email address indicated in the job offer. Consult the job offer for the application email and submission details.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.