AI/ML/Data Science Intern - Computer Vision
jj · Zug
Description du poste
About the role
Johnson & Johnson is looking for a highly skilled and motivated summer intern to join its Computer Vision team in Zug. You will contribute to developing and implementing state-of-the-art AI/ML methods for medical image and video understanding, extracting insights from modalities such as endoscopy and ultrasound videos, X-rays, dermatology/skin images, retinal OCT scans and histopathology slides, and building foundation and multimodal models that generalise across them. The internship lasts 6 months and starts on 1 March 2027.
Key responsibilities
- Conceive, develop and implement interviews with internal clinical personnel to understand needs and use cases for AI tools for medical imaging and video
- Take part in cross-functional interviews, follow up on questions and turn answers into briefing reports
- Extract insights from briefing reports on the business value of AI pipelines across therapeutic areas
- Design, develop and evaluate computer vision and multimodal models on medical imaging and video data
- Explain highly technical methods and results clearly to diverse audiences and partners to support decision-making
Required profile
- Ongoing Master's or PhD in a quantitative discipline (physics, mathematics, computer science, electrical engineering or similar)
- Demonstrated experience driving research in and applying computer vision techniques (Transformers, CNNs, RNNs, GANs)
- Experience with state-of-the-art image and/or video understanding techniques (foundation models, transformers)
- Strong publication record and ability to communicate technical work to a wide audience
Required skills
- Proficiency in Python or C++
- Traditional computer vision: OpenCV, object detection, edge detection, image segmentation
- Machine learning algorithms such as random forest, SVM, boosting and neural networks
- Preferred: medical imaging modalities, foundation models and multimodal AI, familiarity with drug discovery and clinical development, and close work with healthcare professionals
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Zug