Summer 2026 FT Research Fellowship: "Analysis of Stillbirth in South Asia"

The King Center on Global Development's Summer Undergraduate Full-Time Research Assistant Program offers opportunities for fieldwork and research experience to matriculated, Stanford, undergraduates interested in global poverty and development across all academic disciplines.

When Stanford University travel policies allow, selected students spend up to 12 weeks in a low- or middle-income country conducting full-time research for a King Center faculty affiliate. Each research assistant receives a stipend of approximately $8,500 that covers most associated costs including travel, lodging, and incidental expenses.  Financial aid of up to $1,500 is also awarded to students who qualify.

Students are welcome to apply to multiple opportunities but must apply to each faculty research project separately.  Students may only accept one project if they are offered multiple opportunities.

If you have problems submitting your application, please report issues through the SOLO platform with a screenshot that includes the URL and the full page.  Please email kingcenter_programs@stanford.edu to also let us know of your issue(s). 

RESEARCH PROJECT SUMMARY:

There are an estimated 1.9 million stillbirths globally each year, nearly as many as the number of deaths in the neonatal period, i.e., the first 28 days after birth. Despite the large burden and the fact that many stillbirths are preventable through quality antenatal and intrapartum care, stillbirths receive little attention in global policies, programs, research, and funding. In collaboration with local partners, we conducted a population-based study in five sites across Bangladesh, India, and Pakistan, where we identified and followed women of reproductive age to identify pregnancies, pregnancy outcomes, and signs of illness and risk factors for mortality among young infants. We enrolled 71,302 pregnancies and identified 2,320 stillbirths. We conducted a verbal autopsy (VA), i.e., a structured interview with the family to ascertain the context and potential contributory factors, for 1,669 of the stillbirths. Furthermore, a physician review of VAs in Pakistan has provided causes of stillbirths in these data, and we have identified additional studies that contain such information and plan to integrate them into our database. In this project, the student will apply machine learning methods to these datasets with the goal to investigate causes and factors associated with stillbirth. This will provide a novel framework for study of stillbirth that goes beyond current approaches and that can more broadly investigate stillbirth and provide insights into its causes and thus inform approaches to stillbirth prevention.

Research mentor: Assistant Professor Ivana Maric

Dates: A minimum of ten weeks during summer quarter 2026.

WHAT YOU WILL DO: 

The research assistant will work closely together and in collaboration with the research team to:

• Data analysis using machine learning.
• Participate in regular meetings to discuss the project.
• Contribute to preparing a manuscript to describe results.