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Postdoctoral Scientist

3 months ago


New York, New York, United States Johnson & Johnson Full time
Job Description

J&J Innovative Medicine - R&D Data Science Analytics & Insights team is recruiting a Postdoctoral Scientist . The successful candidate will play a role in applying machine learning (ML) and natural language processing (NLP) methodologies to promote data-driven and automated clinical operations across various therapeutic areas. The candidate will leverage, adapt, and extend ML and NLP techniques to build pipelines supporting global clinical operations including site selection. The location for this position is flexible – either; Titusville, NJ; Raritan, NJ; Spring House, PA; Cambridge, MA; New York City, NY; San Diego, CA; South San Francisco, CA; Beerse, Belgium; remote may also be considered.

J&J 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 from clinics to hospitals. To learn more about J&J Innovative Medicine, visit https://

Key responsibilities:
  • Conceive, develop, and implement ML and NLP solutions to high-priority scientific problems,
  • Fine tune and adapt large language models (LLMs) to support clinical trial operation including conducting comparative analytics on clinical trial protocols, trial similarity assessment and eligibility criteria evaluation,
  • Leverage operational data sources and optimization techniques to create tools for developing scenarios with cost and enrollment optimization and deliver related real-world data insights,
  • Contribute to patient modeling and enrollment simulations to have accurate projections for completion of enrollment,
  • Shape internal/external collaborations and define the scope of research questions,
  • Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision-making.