Medical Endoscopy AI Scientist: Vision & Deep Learning

Cosmo Group; Milano; On-site; EUR 95,000 - 125,000; Full time

Job summary

Cosmo Group is seeking a highly skilled Computer Vision & AI Scientist to join our medical AI team. You will advance state-of-the-art in computer vision and deep learning for medical endoscopy, contributing to AI products deployed in hospitals worldwide and used on millions of patients.

The role emphasizes collaboration, rigorous experiments, reproducible research, and opportunities to publish in top conferences and journals, with potential integration of models into medical devices.

Qualifications

• Master's degree or PhD in a relevant field.
• 5+ years of hands-on deep learning and computer vision experience.
• Strong proficiency in Python and PyTorch.
• Proven track record of CV projects with publications, patents or public repos.
• Excellent analytical, problem-solving and communication skills.
• Fluency in English (written and spoken).

Responsibilities

• Collaborate with AI scientists and cross-functional teams to develop AI solutions for medical endoscopy.
• Research, implement, train and evaluate CV and DL approaches for endoscopy video analysis.
• Design experimental protocols and benchmark on large-scale video data.
• Report findings through internal reports, presentations and docs.
• Stay abreast of CV, DL and medical image analysis advances and support publications.
• Contribute to integrating AI models into existing medical devices and systems.

Skills

Python

PyTorch

Collaboration

Education

Master's degree in Computer Science, Engineering, Physics, Math or related

PhD strongly preferred (CV/ML/Medical Imaging)

Tools

GitHub/GitLab

Job description

Cosmo Group is seeking a highly skilled Computer Vision & AI Scientist to join our medical AI team. You will advance state-of-the-art in computer vision and deep learning for medical endoscopy, contributing to AI products deployed in hospitals worldwide and used on millions of patients.

The role emphasizes collaboration, rigorous experiments, reproducible research, and opportunities to publish in top conferences and journals, with potential integration of models into medical devices.