Post Doc - AI/ML and Optimization

At Johnson & Johnson,we believe health is everything.

Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions are personal.Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.Learn more at jnj.com .

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We provide an inclusive work environment where each person is considered as an individual.

At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:
Career Programs

Job Sub Function:
Post Doc - Data Analytics & Computational Sciences

Job Category:
Career Program

All Job Posting Locations:
Cambridge, Massachusetts, United States of America, Titusville, New Jersey, United States of America

Job Description:

About Innovative Medicine

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements.

Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

Learn more at https://www.jnj.com/innovative-medicine

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.

Key Responsibilities


* 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 re...