Stanford University Predoctoral Research Fellowships 2026: Apply for Opportunities in Economics, AI, Health and Climate
Overview
The Stanford University Predoctoral Research Fellowships at the Institute for Economic Policy Research offer early-career researchers and students planning to pursue a PhD an opportunity to work directly with faculty members. The programme provides a platform to engage in research addressing important economic and policy issues across multiple fields, including economics, finance, public policy, health economics, and related areas. Participants contribute to various stages of the research process, helping them build practical skills and gain academic research experience before applying for doctoral programmes.
What you get
Fellows work closely with Stanford researchers on diverse projects covering topics such as immigration, taxation, inequality, health, climate economics, artificial intelligence, international trade, healthcare, finance, economic policy, and digital media. Depending on the assigned project, activities may include building and harmonizing datasets, conducting econometric analysis, undertaking historical research, reviewing academic literature, writing research papers, developing research tools, and producing policy-oriented outputs. One specific position is structured as a one-year appointment with the possibility of renewal for a second year.
Requirements
The positions are suited for candidates aiming to strengthen their quantitative research, programming, data analysis, and academic research experience. Applicants are expected to have strong quantitative, programming, analytical, and research skills, which may include experience with Python, R, Stata, Julia, or SQL, as well as econometric analysis, large-scale datasets, causal inference, data visualization, historical research, academic literature reviews, research writing, and artificial intelligence tools. Specific projects have distinct preferences; for instance, certain roles require prior coding experience and a strong quantitative and programming background, while others welcome backgrounds in mathematics and computer science without requiring prior economics training.