. We are seeking a person with excellent skills in transmission-dynamic modeling and parameter inference, including appropriate programming skills in one or more of R, Python, C++. The first project for this postdoctoral fellow would be a systematic comparison of the performance of inferential methods for detecting intervention effects (vaccination, behavioral change) in observed time series of infectious disease data, starting with single-strain diseases and possibly moving on to multi-strain systems, a particular interest of our group. The postdoctoral fellow will also have opportunities to work on other projects of interest, including theoretical models of multiple-strain pathogens, use of models to account for heterogeneity in risk and intervention effectiveness during intervention trials, and projects arising as the result of emergence of new public health threats. The position is in the research group of Marc Lipsitch, CCDD Director, with co-supervision from Caroline Buckee, Associate Director.
School: Harvard T.H. Chan School of Public Health
Department: Center for Communicable Disease Dynamics
Skills in one or more areas R, Python, C++
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, or any other characteristic protected by law.