Post-Doctoral Scientist

Johnson & Johnson Innovative Medicine Research & Development (R&D), is recruiting for a Post-Doctoral Scientist, Data Science RWE Advanced Analytics . The primary location for this position is flexible - either; Titusville, NJ; Raritan, NJ; Spring House, PA; Cambridge, MA; San Diego, CA; South San Francisco, CA; Beerse, Belgium; remote may also be considered. Johnson & Johnson Innovative Medicine develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, cardiovascular and metabolic disorders, immunology, pulmonary hypertension, 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 clinics to hospitals. To learn more about Johnson & Johnson Innovative Medicine, visit The R&D Data Science RWE Advanced Analytics team within J&J develops innovative solutions using various data sources across multiple disease areas in support of J&J's key clinical programs. We are looking for an outstanding post-doctoral scientist whose responsibilities will include the development of groundbreaking methodologies to develop RWD-based solutions to enable disease insights, improve patient outcomes, and enhance clinical development. Key Responsibilities: Lead and assist in answering critical questions in clinical development using pioneering modeling & simulation methodologies, critical decision-making like study design, dose selection, adaptive designs, etc. based on real-world data (RWD) and clinical trials. Development of artificial intelligence/machine learning models in healthcare (e.g., disease identification, patient stratification, disease progression, forecasting) based on RWD that will provide key insights into our pipeline assets Leverage emerging scientific and technological developments to generate new research ideas, solutions, and initiatives using real-world data (electronic health records, insurance claims, registry data, others) Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision-making