Data Science Postdoc, Medical Imaging Computer Vision
Janssen Research & Development LLC, a Johnson & Johnson company, is recruiting for a postdoc located in the US (Cambridge, MA; Titusville, NJ; Raritan, NJ; La Jolla, CA; or Spring House, PA) or Europe (Beerse, Belgium; Zug, Switzerland). Remote positions will also be considered.
Janssen develops treatments that improve the health of people worldwide. Research and development areas encompass 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. To learn more about Janssen, one of the Pharmaceutical Companies of Johnson & Johnson, visit www.janssenpharmaceuticalsinc.com.
We are looking for talented and driven individuals to join our Video Understanding team at Johnson & Johnson. As a postdoctoral researcher, you will have the exciting opportunity to contribute to the development and implementation of advanced AI/ML methods for medical video understanding. Your role will involve applying sophisticated AI techniques to extract valuable insights from different medical video modalities like endoscopy, ultrasound, and echocardiogram. Through the use of these innovative technologies, you will improve our understanding of medical procedures and interventions, ultimately enhancing clinical trial efficacy and efficiency.
The Data Science Analytics & Insights team within Janssen R&D develops innovative solutions using a variety of data sources across multiple different disease areas. We are looking for an outstanding postdoc with a focus on Radiology Computer Vision.
Key Responsibilities:
- Conceive, develop, and implement video understanding computer vision solutions to high-priority scientific problems
- Participate in cross-functional collaborations with external companies and internal scientific, clinical, and data science teams
- Shape internal/external collaborations and define the scope of research questions
- Extract insight from complex, unstructured medical image and videos to improve drug discovery and healthcare (e.g., disease identification, patient stratification, disease insights)
- Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision-making
