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
Job Description:Johnson & Johnson Innovative Medicine is recruiting for
Postdoctoral Scientist,R&D DDSAI, Real-World Evidence (RWE) NeurologyAbout 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
The
Real-World Evidence (RWE) Neurology team within Johnson & Johnson Innovative Medicine is seeking an outstanding postdoctoral scientist to help develop real-world evidence methods to support neuroscience clinical development.
This role will focus on building practical, reusable approaches to evaluate whether artificial intelligence and machine learning outputs are
robust, interpretable, and fit-for-purpose when applied to clinical-development regulatory grade questions. The postdoctoral scientist will work at the intersection of real-world data, historical clinical trial data, clinical outcomes, biomarkers, and selected multimodal data sources to support patient characterization, disease-trajectory modeling, endpoint assessment, and evidence generation for regulatory and clinical decision-making.
Key ResponsibilitiesThe postdoctoral scientist will contribute to projects that may include:
- Analyze real-world data sources, observational databases, registries, and historical clinical trial data to generate insights supporting neuroscience clinical development and regulatory evidence strategies.
- Develop and apply statistical and machine learning methods to support patient subtyping, disease-progression modeling, endpoint evaluation, treatment-pattern characterization, and clinical trial design.
- Evaluate model robustness and stability under clinically meaningful changes, such as cohort definitions, biomarker thresholds, endpoint assumptions, missingness patterns, or patient-selection criteria.
- Support development of interpretable and transparent modeling workflows, including model documentation, sensitivity analyses, bias assessment, and reproducibility checks.
- Integrate structured clinical data with selected multimodal inputs, such as biomarkers, clinical narratives, digital measures, or literature-derived features, where appropriate and feasible.
- Conduct literature reviews to contextualize disease biology, clinical endpoints, real-world evidence methods, and emerging artificial intelligence approaches in neuroscience.
- Create study protocols, statistical analysis plans, analysis-ready datasets, tables, figures, and technical reports.
- Collaborate with cross-functional partners, including statistics, data science, clinical development, translational science, regulatory, epidemiology, and medical affairs teams.
- Communicate technical results clearly to both quantitative and non-technical audiences through presentations, written reports, and scientific publications.
Required Qualifications- Ph.D. or equivalent doctoral degree in biostatistics, statistics, epidemiology, data science, biomedical informatics, computer science, computational biology, bioengineering, or a related quantitative discipline.
- Strong programming skills in R and/or Python, with experience analyzing patient-level healthcare or clinical data.
- Experience with statistical modeling, machine learning, or causal inference methods applied to biomedical, clinical, or real-world data.
- Hands-on experience with data extraction, cleaning, transformation, quality control, and reproducible analysis workflows.
- Familiarity with methods to address confounding, selection bias, missing data, measurement error, or other sources of uncertainty in observational studies.
- Strong written and verbal communication skills, with the ability to explain quantitative methods and results to multidisciplinary audiences.
- Demonstrated ability to work collaboratively in a team-based scientific environment.
Preferred Qualifications- Experience with real-world data sources, such as electronic health records, insurance claims, patient registries, natural history studies, or other observational datasets.
- Familiarity with clinical trial data structures, clinical endpoints, biomarker data, or regulatory evidence-generation workflows.
- Experience with machine learning methods such as regularized regression, tree-based models, gradient boosting, survival models, representation learning, or explainable artificial intelligence methods.
- Experience conducting sensitivity analyses, model validation, robustness checks, or reproducibility assessments.
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Required Skills:Preferred Skills:The anticipated base pay range for this position is :$79,000.00 - $127,650.00
Additional Description for Pay Transparency:
Subject to the terms of their respective plans, employees are eligible to participate in the Company's consolidated retirement plan (pension) and savings plan (401(k)).
Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits:
Vacation -120 hours per calendar year
Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado -48 hours per calendar year; for employees who reside in the State of Washington -56 hours per calendar year
Holiday pay, including Floating Holidays -13 days per calendar year
Work, Personal and Family Time - up to 40 hours per calendar year
Parental Leave - 480 hours within one year of the birth/adoption/foster care of a child
Bereavement Leave - 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
Caregiver Leave - 80 hours in a 52-week rolling period10 days
Volunteer Leave - 32 hours per calendar year
Military Spouse Time-Off - 80 hours per calendar year
For additional general information on Company benefits, please go to: - https://www.careers.jnj.com/employee-benefits
