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Sonio

AI-powered fetal ultrasound software for diagnosis

Data Science Intern

Computer VisionPosted on Nov 10
InternshipÎle-de-France, FranceNo salary listedHybrid

About the Job

Requirements

  • Currently pursuing Master 2 / Bac+5 at an engineering school or university, majoring in Computer Science or Data Science, and seeking an internship lasting 5 to 6 months.
  • Good knowledge of Machine Learning and Deep Learning algorithms, and willingness to explore and work with state-of-the-art algorithms.
  • Solid Python and PyTorch/Hugging Face skills, and familiarity with segmentation and detection architectures.
  • Strong interest in computer vision and women's health.
  • Ability to speak English; French is ideally desired.

Responsibilities

  • Develop clinical understanding of fetal ultrasound in the anatomical areas assigned.
  • Explore and train approaches for detection and segmentation of anatomical structures and views, and integrate results into the machine-learning infrastructure (AWS, SageMaker, and MLflow).
  • Explore the possibility of training foundation models for ultrasound imaging.
  • Run evaluation protocols consistent with the evaluation of models during regulatory submissions, and document experiments for the team to build on them.
  • Potentially publish results if they support publication.

Desired Qualifications

  • A first experience with medical images is a plus.
  • French language ability is ideal.

About the Company

Sonio

AI-powered fetal ultrasound software for diagnosis

Sonio develops AI-based fetal ultrasound software to assist clinicians in analyzing prenatal ultrasound images and diagnosing congenital malformations. The software blends ultrasound semiology with patient medical history, genetic and biological data to provide decision support and guide physicians toward the most likely diagnosis, while also assisting sonographers during prenatal screening scans. It integrates into clinical workflows to deliver timely insights for healthcare providers and support for mothers and their babies. Unlike tools that rely on a single data type, Sonio combines multiple sources of information to help practitioners interpret scans more accurately and efficiently. The company’s goal is to improve the accuracy and speed of fetal anomaly screening and enhance maternal-fetal health outcomes.

Company size
51-200
Company stage
Acquired
Total funding
$19.5M
Headquarters
Paris, France
Founded
2020

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