The Department of Biostatistics at Harvard TH Chan School of Public Health invites applications for a postdoctoral fellow position focused on the development of statistical methods for climate epidemiology. Working with an interdisciplinary team of statisticians, epidemiologists, environmental scientists, and clinicians, the fellow will develop practical statistical methods and apply them to real data with the goals of (1) quantifying the health impacts of historic extreme climate events such as tropical cyclones, flooding, and heat waves; (2) identifying key social, economic, environmental, and health modifiers of these effects; and (3) predicting the health burden of future extreme climate events. This research will improve our understanding of climate epidemiology, inform strategic preparedness efforts to minimize the adverse health impacts of future extreme climate events, and will generate novel and broadly applicable statistical and computational tools.
This position will involve the development and implementation of methods at the intersection of causal inference, spatio-temporal modeling, and machine learning in response to challenges presented by our rich integrated health and climate exposure datasets. These data include health outcomes from Medicare and Medicaid claims and birth cohorts and high-resolution multi-decade climate exposure metrics. In addition to methods development and data analysis, the fellow will be expected to write and publish peer-reviewed scientific papers, participate in group meetings and collaborative projects, and mentor more junior team members. The ideal candidate will have a strong statistical and computational background, experience processing and analyzing large datasets, and outstanding communication skills. The postdoctoral fellow will be supervised by Dr. Rachel Nethery at Harvard and will work closely with collaborators across multiple institutions.
Doctoral degree in Biostatistics, Applied Statistics, Computer Science, or related field
Experience developing and implementing statistical methods
Experience analyzing real data
Strong programming skills
Excellent communication and writing skills
Demonstrated ability to publish peer-reviewed scientific papers
Commitment to collaborative work
Experience implementing Bayesian models
Experience working with spatial data
Experience processing and analyzing large datasets
Experience creating R packages and utilizing version control systems, e.g., Git/Github
Contact Email: firstname.lastname@example.org
One-page research statement and/or one representative first author publication
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.
Internal Number: 9845
About Harvard University
Harvard University is devoted to excellence in teaching, learning, and research, and to developing leaders in many disciplines who make a difference globally. The University, which is based in Cambridge and Boston, Massachusetts, has an enrollment of over 20,000 degree candidates, including undergraduate, graduate, and professional students. Harvard has more than 360,000 alumni around the world. The University has twelve degree-granting Schools in addition to the Radcliffe Institute for Advanced Study, offering a truly global education. Established in 1636, Harvard is the oldest institution of higher education in the United States.