Title: Postdoctoral Fellow for Statistical Methods in EHR-Based Studies
School: Harvard T.H. Chan School of Public Health
Position Description: This is a postdoctoral position with the scientific goals being the development, implementation, and evaluation of statistical methods for causal inference based on electronic health records ( EHR ) data. The postdoctoral fellow will work with Drs. Haneuse, Mukherjee, and Wang in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health, as well as their collaborators at Kaiser Permanente. The focus of the work will be on semi-parametric methods for handling missing data in EHR -based settings but may extend beyond, and will involve hands-on analysis of long-term outcomes following bariatric surgery.
Basic Qualifications: Doctoral degree in Biostatistics, Statistics, Computer Science, or a related field. Strong theoretical and programming skills (e.g., R, C++, Python, Julia) are required and experience with EHR data is a plus.
Contact Information: Trevor Bierig
Contact Email:
biostat_postdoc@hsph.harvard.edu
Equal Opportunity Employer: We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law.
Minimum Number of References Required: 2
Maximum Number of References Allowed: 4
Supplemental Questions: Required fields are indicated with an asterisk (*).
