Postdoctoral Fellow for Statistical Methods at the Intersection of Randomized Trials and Observational Studies
School: Harvard T.H. Chan School of Public Health
Position DescriptionThis is a postdoctoral position with the scientific goals being the development, implementation, and evaluation of statistical methods for causal inference. Specifically, the focus of the work will be on frequentist and/or Bayesian methods that seek to use ideas from clinical trials design and analysis (including group sequential methods and adaptive trial designs) to causal inference based on observational data. The postdoctoral fellow will work with Drs. Haneuse, Trippa, and Hejazi in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health.
Basic QualificationsDoctoral 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 InformationTrevor Bierig
Contact Email: firstname.lastname@example.org
Equal Opportunity EmployerWe 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