Postdoctoral Fellow, Epidemiology & Oncology RWE

Description

The appropriate use of Real-World Data (RWD) across the full cycle of drug development is crucial in the pharmaceutical industry. Pharma R&D is increasingly using RWD in the pre-market setting to inform clinical development programs and support regulatory submissions.

At AstraZeneca (AZ), the clinical data sciences and real-world evidence (RWE) team within the broader AZ Oncology Data Science organization ensures all Phase 2-3 clinical trials, from investment decisions through regulatory filing and commercialization are informed with robust Real World Evidence (RWE). While our day-to-day work generates RWE for internal decision-making on clinical trial study development and interpretation (, control arm selection, expected control arm performance, study population definitions, trial interim analyses), our work is increasingly encouraged to impact regulatory submissions, providing supportive and eventually pivotal evidence. Collected from various sources such as electronic health records and medical claims for non-research purposes, RWD has limitations versus RCTs. We strive to use thorough study design and leverage the best methods to control numerous sources of bias that arise with non-randomized study designs. Furthermore, in oncology drug development, databases of NGS-tested patients rich in molecular data coupled with clinical data have huge potential, but require additional development and application of novel methods to understand their relevance to AZ trials.

This postdoc position has a duration of up to three years.

Role Summary

Do you have expertise in, and a passion for, the development and application of advanced epidemiology methods to ensure rigorous insights for patients? Would you like to apply your expertise to impact early and late oncology clinical development in an organization that follows the science and turns ideas into life-changing medicines?

Purpose of this Position

To realize AstraZeneca oncology’s long-term strategic goals to leverage Real World Data to accelerate drug development, we seek a postdoctoral researcher to develop, adapt, and rigorously evaluate epidemiological methods for bias correction to ensure our study findings are relevant and comparable to clinical trials and ultimately fit to support FDA submissions.

What's Involved in the Role

The postdoc will design and implement several demonstration projects, testing approaches to correct or minimize the impact of various biases we encounter in our day-to-day use of claims, electronic health records, and multi-modal data. Results from these methods will be compared to AZ's status-quo analytic approaches and validated against historical clinical trials' SoC arms!

Why Should You Apply?

You will have the opportunity to formulate and address key scientific questions motivated by AstraZeneca’s oncology portfolio strategy. These questions will drive innovative research of broad interest to the pharmacoepidemiology and clinical-genomics scientific communities. You will produce high-impact publications on innovative research questions in the fields of pharmacoepidemiology and causal inference and simultaneously advance AstraZeneca’s use of RWE to accelerate and streamline drug development. Furthermore, you will have access to extensive sources of RWD and clinical trial data, and the support of teams with in-depth knowledge of data sources, clinical expertise, and mentorship from internal and external methods experts.

Collaborations

You’ll join a highly motivated, fast-paced team of epidemiologists and data scientists committed to rigorous research, bringing novel RWD insights to AstraZeneca’s Oncology pipeline. Your experience will be enriched through collaboration with a diverse internal community, including statistical innovation, applied data science, artificial intelligence, clinical teams, and the broader community of AstraZeneca postdocs. In addition to the team at AstraZeneca, you will have the opportunity to be mentored by two academic advisors, Dr. Issa Dahabreh from the Chan Harvard School of Public Health, and Dr. Camille Maringe at the London School of Hygiene and Tropical Medicine.

Essential Skills, Experience & Behaviors

• Solid understanding of epidemiological study design.
• Experience or knowledge of working with Real World Data such as claims, electronic health records, or experience with analyzing clinical trial data.
• Significant experience with bias and methods to correct bias, such as propensity score weighting / matching, instrumental variable analysis, matching adjusted indirect comparisons, etc.
• Familiarity with approaches for generalizability and transportability.
• Experience coding in R (or similar).

Essential Qualifications / Education

PhD in fields such as Epidemiology, Pharmacoepidemiology, Biostatistics, Statistical Genetics, Clinical Informatics, Computer Science, Health Informatics.

Desirable Skills, Experience & Behaviors

Personal Characteristics & Behaviors

We anticipate a high volume of applicants, so do not delay, apply today!

Compensation for this role, is based on years of experience after obtaining PhD, is a minimum of $107,500 up to a maximum of $120,000 + short-term incentive. Some relocation supplements depend on distance and location at the employer's discretion.

Date Posted

15-Oct-2025

Closing Date

Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.