Data Science Postdoc, Ophthalmology Imaging

J&J Innovative Medicine develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, cardiovascular and metabolic disorders, retina, 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.

Preferred Location: Raritan, NJ; San Diego, CA ; Cambridge, MA; Spring House, PA

We are looking for talented and driven individuals to join our computer vision Imaging 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 analyzing images in ophthalmology and retina. Your role will involve applying state-of-the-art AI techniques to extract valuable insights from various image modalities such as OCT (optical coherence tomography), FAF (fundus auto-fluorescence), and CFP (color fundus photography) in diseases such as dry AMD and IRDs. Through the use of these innovative technologies, you will improve our understanding of structural biomarkers during disease progression, ultimately enhancing clinical trial efficacy and efficiency.

The Data Science Analytics & Insights team within J&J Innovative Medicine 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 ophthalmic imaging in computer vision.

Key Responsibilities:

• Conceive, develop, and implement image analysis 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 multi-modal images 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.