Post Doc - AI​/ML and Optimization

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Job Function:
Career Programs. Job Sub Function:
Post Doc – Data Analytics & Computational Sciences. Job Category:
Career Program.

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Cambridge, Massachusetts, United States of America;
Titusville, New Jersey, United States of America.

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J&J Innovative Medicine
- Data, Data Science, and AI
- Global Development (DDSAI GD) is recruiting a Postdoctoral Scientist - AI/ML and Optimization. The ideal candidate will apply machine learning (ML), generative AI (GenAI), and optimization techniques to develop computational solutions that support and enhance global clinical operations, including enrollment forecasting, cost estimation and optimization, and country and site selection.

• Conduct research, build, test, and improve ML, GenAI, optimization pipelines for clinical development and trial operations.
• Analyze, prepare, and leverage operational, RWD, and cost data to build ML models and optimization engines to
  1) predict outcomes of interest,
  2) highlight tradeoffs between competing trial objectives,
  3) recommend optimal operational scenarios, and
  4) generate actionable insights, enabling early intervention and risk management.
• Develop and evaluate LLM-enabled workflows for document extraction, protocol comparison, trial similarity assessment, data harmonization, clinical-concept interpretation, and eligibility-criteria assessment.
• Stochastic simulations to forecast operational and patient journey outcomes including enrollment and patient study completion.
• Design experiments and tailored evaluation metrics and frameworks to support validation, monitoring, data-quality, and responsible-AI practices.
• Contribute reusable code, data pipelines, documentation in collaboration with data scientists, engineers, and clinical‑development partners.
• Communicate research findings, analytical methods, and recommendations clearly to technical and non‑technical stakeholders and contribute to internal or external scientific dissemination.

• A Ph.D. degree, completed or expected before the start date, in computer science, statistics, biostatistics, biomedical informatics, epidemiology, health economics, applied mathematics, engineering, or another quantitative discipline.
• Hands‑on experience with multi‑modal ML predictive modeling and stochastic simulations for time‑series forecasting.
• Experience with GenAI and clinical LLMs for document parsing, clinical concept disambiguation, or harmonization.
• Experience building multi‑objective optimization engines to navigate…