Title Postdoctoral Research Fellow
School Harvard T.H. Chan School of Public Health
The Departments of Nutrition and Biostatistics at the Harvard T.H. Chan School
of Public Health invite applications for a Postdoctoral Fellow for statistical
methods development and application to examine the human health impacts of
environmental change in Madagascar. Expertise in causal inference and machine
learning is desirable but not necessary. The position will work with a multi-
disciplinary team with expertise in statistical methods, ecology,
epidemiology, climate science, and planetary health. The position will be
under the joint supervision of Dr. Christopher Golden in the Department of
Nutrition and Dr. Francesca Dominici in the Department of Biostatistics.
Applicants should have an interest in developing and applying novel and state-
of-the-art statistical and data science methods in planetary health. This
research fellowship will last for at least 2 years pending successful
performance in the first year. The post-doc will be based in Boston, where we
have a rich community of researchers investigating the interrelationship of
ecosystem transformation and human health.
Search: We are looking to hire a researcher with a strong data science
and/or epidemiological background to 1) integrate climate (e.g.,
temperature, rainfall, soil moisture), environmental (e.g., forest cover,
agricultural production, land use change), and health (e.g., monthly
incidence data for 23 conditions from more than 3,000 clinics) data; and 2)
analyze exposure pathways that connect climate and environmental data to
Duties and Responsibilities
The position will contribute to the effort of:
· Collaborate with a data engineer to integrate the aforementioned data
streams into an interoperable research data platform
· Liaise between the Ministry of Health in Madagascar and the HSPH research
team to develop research question priorities
· Use cutting-edge statistical methods for big data to analyze the human
health impacts of environmental change
· Write up research reports for the Ministry and for peer-reviewed publication
· Collaborate with our biostatistics and data science group
· Doctoral degree in Computer Science, Statistics, Biostatistics, or related
· Experience analyzing real data with strong programming skills
· Excellent communication and writing skills.
· Experience in handling very large spatial datasets.
· Experience in applied statistics and computational methods.
· Knowledge of R, SAS, and Python.
· Skills in remote sensing data applications strongly preferred
Familiarity with multiple data science tools and ability to learn new
tools as required.
Experience with version control systems, in particular Git and GitHub.
Interest in open-source software, reproducibility and data management.
The ideal candidate is an independent, solution-oriented thinker with a
strong background processing very large data sets, applying analytical
rigor and statistical methods, and driving toward actionable insights and
· Preference for strong skills in data visualization for figures and/or web
To apply: Please submit a CV and brief cover letter detailing relevant
experience and reason for interest in the project to Dr. Chris Golden
(email@example.com). Please also send the names of three
references. Applications are due by December 20th though may be
considered thereafter. Interviewing will take place in late January.
Position will start between April and September 2022.
Dr. Christopher Golden, Assistant Professor of Nutrition and Planetary Health
Contact Email firstname.lastname@example.org
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 3
Maximum Number of References Allowed 5
Required fields are indicated with an asterisk ().
Statement of Research