Postdoctoral Researcher Video team

Conceive, develop, and implement ideas with key internal clinical personnel to understand needs and use cases around AI tools for endoscopy. Design, develop, and evaluate deep learning models for medical video and image understanding (scoring, segmentation, and detection). Lead the research and development of uncertainty quantification methods for model predictions (e.g., Bayesian approaches, ensembles, calibration metrics, and predictive intervals) and integrate uncertainty estimates to quantify the reliability and confidence of AI-driven diagnostic model outputs. Develop advanced multi-modal models for video analysis, integrating data from endoscopy, ultrasound, intestinal ultrasound (IUS), and Magnetic Resonance Enterography (MRE). Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision-making. Participate in cross-functional team meetings, drive discussion and follow-up questions to collaborators, and compile answers into briefing reports. Extract insights from collection of briefing reports focusing on business value of AI pipelines for immunology.

Janssen Research & Development LLC, a Johnson & Johnson company, is recruiting a postdoctoral researcher to join the Video Understanding team. Positions are available in the US (Titusville, NJ; Raritan, NJ; La Jolla, CA; Cambridge, MA; New York, NY; Spring House, PA) or Europe (UK, Netherlands, Switzerland, Austria). Remote arrangements will also be considered. Janssen develops treatments that improve the health of people worldwide. Our research spans oncology, cardiovascular and metabolic disorders, immunology, neuroscience, and infectious disease. Our goal is to help people live longer, healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market – from patients to practitioners and from clinics to hospitals.

• 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.