Postdoctoral Research Associate

About the Role

Seeking a highly motivated Postdoctoral Researcher to develop innovative statistical methods for pediatric oncology clinical trials. Research focuses on methodological challenges in pediatric and rare-disease settings.

Key Responsibilities

• Develop new statistical methodology motivated by important pediatric oncology problems.
• Conduct simulation studies to evaluate statistical operating characteristics.
• Analyze clinical trial, registry, and real-world datasets.
• Develop statistical software in R and/or Python.
• Collaborate closely with pediatric oncologists, clinical investigators, statisticians, and data scientists.
• Participate in the design and analysis of innovative pediatric oncology clinical trials.
• Publish methodological and applied research in leading statistical, clinical trial, and medical journals.
• Present research at national and international scientific meetings.
• Develop independent research ideas and a coherent methodological research program.
• Contribute to collaborative grant proposals and future independent funding applications.
• Participate in mentoring and research activities within the Department of Biostatistics.

Research Areas

Potential areas of methodological research include:

• Innovative Clinical Trial Design: Developing efficient and rigorous statistical methods for early- and mid-phase pediatric oncology trials.
• Causal Inference, External Controls, and Real-World Evidence: Developing principled approaches for incorporating external information into clinical trials.
• Digital Twins and Counterfactual Prediction: Developing and evaluating digital twins and counterfactual prediction methods for clinical trials.
• Survival, Longitudinal, and Complex Clinical Outcomes: Developing new statistical methodology for delayed, longitudinal, multistate, or otherwise complex outcomes.

Requirements & Tech Stack

• Strong quantitative training with interest in developing statistical methodology.
• Experience with statistical programming, preferably in R and/or Python.
• Strong written and oral communication skills.
• Ability to work effectively in multidisciplinary research teams.
• Interest in clinical trials and biomedical research.

Qualifications

• PhD in biostatistics, statistics, epidemiology, data science, or a closely related quantitative discipline.
• Strong training in statistical methodology.

Experience in one or more of the following areas would be particularly valuable:

• Clinical trial design
• Survival analysis
• Bayesian statistics
• Causal inference
• External controls or real-world evidence
• Target trial emulation
• Longitudinal data analysis
• Machine learning or causal prediction
• Pediatric oncology

Prior experience in pediatric oncology is not required. Candidates with strong methodological training interested in developing expertise in pediatric cancer research are encouraged to apply.