Postdoctoral Researcher, Video Team

Responsibilities

• Design, implement, and evaluate state‑of‑the‑art AI/ML methods for video‑level understanding across diverse medical modalities.
• Collaborate closely with clinicians, engineers, and data scientists to translate advanced algorithms into robust, interpretable AI tools.
• Conceive, develop, and implement ideas with key internal clinical personnel to understand needs for AI tools.
• Lead the research and development of uncertainty quantification methods for model predictions.
• Develop advanced multi‑modal models for video analysis, integrating data from multiple sources.
• Participate in cross‑functional team meetings and drive discussions to compile briefing reports.

• A Ph.D. degree in a quantitative discipline (e.g., Physics, mathematics, computer science, electrical engineering, or similar).
• Demonstrated experience driving research in and applying Computer Vision techniques (e.g., Transformers, CNNs, RNNs, GANs).
• Proven expertise in uncertainty model and measures development, including techniques for uncertainty quantification in deep learning.
• Demonstrated experience on state‑of‑the‑art techniques for video understanding (e.g., foundational models, transformers).
• Proficiency with one or more programming language such as Python or C++.
• Extensive experience with traditional Computer Vision applications, such as OpenCV, object detection, edge detection, image segmentation.
• Experience with machine learning algorithms, including random forest, SVM, boosting, neural networks, etc.
• Strong publication record and ability to effectively communicate technical work to a wide audience.

Expertise in AI/ML methods for video‑level understanding, with a strong focus on uncertainty quantification and computer vision techniques. Proven ability to collaborate with cross‑functional teams and communicate complex technical concepts effectively.