Applied Biostatistics Postdoc - Clinical Trial Simulation

Boehringer Ingelheim GmbH; Ridgefield, Northern (CT, KY); Hybrid; USD 68,000 - 92,000; Full time

Job summary

Boehringer Ingelheim invites applications for a Postdoctoral Medical Fellow in Applied Biostatistics and Clinical Trial Simulation. The role centers on advancing trial simulation tools by integrating multimodal datasets and rigorous statistical methodology from research to practical, decision-support tools.

Candidate will develop scalable pipelines, assess operational and clinical factors, and report results to cross-functional teams, with an emphasis on transparency and reproducibility.

Qualifications

• PhD in Biostatistics or Statistics from an accredited institution, awarded before start date.
• Strong foundation in clinical trial methodology and inference (GLMs, mixed models, survival analysis).
• Program in R and/or Python for statistical modeling and simulation; reproducible workflows preferred.

Responsibilities

• Integrate multimodal data sources to parameterize simulations and inform trial design decisions.
• Evaluate and validate clinical trial simulation frameworks under various operational conditions.
• Build scenario engines for trial execution planning and translate results into decision support.
• Implement and compare statistical methods for robustness, including missing data, Bayesian models, estimands, and site-level effects.
• Create reusable, reproducible simulation pipelines (R/Python) with version control and documentation.
• Communicate results to cross-functional teams via manuscripts, abstracts, and presentations.

Skills

R

Python

Statistical modeling

Git & workflows

Monte Carlo simulation

Bayesian methods

Multimodal data

Clinical trial design

Education

PhD in Biostatistics or Statistics

Tools

Git

Jupyter

R environment

Job description

Boehringer Ingelheim invites applications for a Postdoctoral Medical Fellow in Applied Biostatistics and Clinical Trial Simulation. The role centers on advancing trial simulation tools by integrating multimodal datasets and rigorous statistical methodology from research to practical, decision-support tools.

Candidate will develop scalable pipelines, assess operational and clinical factors, and report results to cross-functional teams, with an emphasis on transparency and reproducibility.