Applications are open for Postdoctoral Research Fellowship at Chapman University in the United States of America. This is an exciting opportunity for a suitably qualified applicant to join the School of Pharmacy at Chapman University as a postdoc research fellow/visiting scholar in Social & Administrative Sciences (SAS) to work with Dr. Sherry Wang. This position is available immediately, although the start date is flexible. The role will be located at Chapman University Rinker Campus in Orange, California.

Summary

The duties of the post will include analysis of high-dimension geospatial data and healthcare data penetrating to the healthcare environment, and development, implementation, evaluation, and application of real-world data in opioids, Covid-19, and other healthcare research.

Candidates will be benefited from joining a strong, international collaborative working group from multiple universities in and out of California and accessing data from large claims data and electronic health records. Moreover, the Department of Biomedical & Pharmaceutical Sciences is looking to appoint an individual with a background in epidemiology, with solid skills and experience in biostatistics and geospatial methods. The candidate will also collaborate closely with epidemiologists, biostatisticians, pharmacists, programmers, and other scientists within the department and, more broadly within the collaborative working group. More information about Dr. Sherry Wang is available at https://www.chapman.edu/our-faculty/sherry-yun-wang

Requirements 

The position is ideal for the candidates who hold or expect to hold a Ph.D. The Ph.D. should be in biostatistics, epidemiology, geospatial science, or a closely aligned quantitative field. All-but-dissertation Candidates who have not yet been officially awarded their Ph.D. can also apply however their degree must be conferred prior to their start date.

• Ph.D. degree in Epidemiology, Biostatistics, or a closely related quantitative discipline.
• Experience in handling big datasets from epidemiological studies, including geospatial and claims data.
• A thorough understanding of applied and emerging statistical methods in the context of real-world data.
• A good understanding of statistical methods for geospatial epidemiology (e.g., ArcGIS and preferably SaTScan).
• Experience in programming in statistical packages (e.g., Stata, R, SAS). Similarly, experience in writing and preparing manuscripts for publication.
• Furthermore, thorough understanding and knowledge of epidemiological study design.

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