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Harvard University Postdoctoral Fellow in Perinatal Epidemiology in Cambridge, Massachusetts

Title Postdoctoral Fellow in Perinatal Epidemiology

School Harvard T.H. Chan School of Public Health

Department/Area Epidemiology

Position Description

The HaSET (“happiness” in Amharic”) Global Maternal and Child Health Research Program at the Harvard Chan School of Public Health and Boston Children’s Hospital invites applications for a postdoctoral fellow. Our program works closely with partners in Ethiopia and Ethiopia’s Federal Ministry of Health to generate evidence to improve maternal and child health programs and policies. We provide technical capacity building in program implementation, data analysis, and use of evidence through direct collaborative work and workshops. HaSET is also a member of the Bill & Melinda Gates-funded Antenatal Care/Postnatal Care Research Collective (ARC). ARC is a multi-country collaborative seeking to build a high-dimensional longitudinal clinical dataset and develop/test 1) models to predict risk and understand mechanisms of causality, 2) interventions to improve health outcomes, and 3) approaches to addressing intractable challenges across the maternal and newborn health continuum of care.

Research will be conducted jointly by the Harvard School of Public Health, Boston Children’s Hospital, St. Paul’s Hospital Millennium Medical College, the Ethiopian Public Health Institute, and other Ethiopian institutions. The Postdoctoral Researcher will have opportunities to analyze large-scale datasets, including pregnancy and birth cohort data. Under the mentorship of Professor Grace Chan, the successful candidate will be developing and validating pregnancy risk stratification models for perinatal mortality, preterm birth, and/or other adverse outcomes. The candidate will work with the team and experts at Harvard to generate mechanistic models of risk by developing and applying causal inference methods to site-specific and pooled data to determine potential causes of morbidity and mortality to shape interventions.

The successful candidate will also join the HaSET fellowship program, which offers teaching opportunities and partnerships with Ethiopian postdoctoral fellows. The candidate will work closely with the growing Boston and Ethiopia-based research teams comprising program managers, data analysts, field implementers, data system developers, trainees and faculty on the HaSET team.

The position is based in Boston with frequent travel to Ethiopia. Commitment is for two years with the potential for renewal.

Basic Qualifications

Doctoral qualification in epidemiology, statistics, public health, or a related field with 2+ years research experience. The ideal candidate will have experience conducting research in global health, particularly in low-and-middle-income countries (LMIC).

Desired skills include:

● Excellent analytical, organizational, and problem-solving skills ● Knowledge of study design, sampling approaches and sample size estimation, descriptive and advanced statistical methods and modeling such as longitudinal data analysis, causal inference methods, complex survey analysis etc. ● Experience analyzing prospective cohort and health surveillance system data. ● Experience cleaning and managing large complex datasets. ● Knowledge of STATA, R, and data systems (e.g., web-based electronic data capture system such as REDCAP or ODK). ● Excellent interpersonal and oral and written communication skills. ● Ability to work independently and as part of a team with collaborators, stakeholders, and research staff.
● Research experience in global maternal and child health, particularly in East Africa, is an asset.

Additional Qualifications

The position is based in Boston with frequent travel to Ethiopia. Commitment is for two years with the potential for renewal.

Special Instructions

Applications should include a cover letter, curriculum vitae, a statement of research, and three reference letters.

Contact Information

Jenna Daniel, HaSET Program Coordinator

Contact Email

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 4

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