Research Policy Associate I

PREDOCTORAL RESEARCHER, Economics, to support work at all stages of the research process on projects in economics and applied machine learning / artificial intelligence. This position offers the opportunity to gain exposure to and training in a broad set of statistical methods and economic research topics. Predoctoral Researchers will engage directly in the research process, and implement complete project pipelines covering data processing, machine learning, and statistical inference. Predoctoral Researchers will work on research projects with Professors Sendhil Mullainathan and Ashesh Rambachan along with their co-authors at MIT, the University of Chicago, Harvard University and other institutions. The role will entail close collaboration with all stages of the research process on projects that integrate machine learning / artificial intelligence and economics. These positions will be part of BikeShop@MIT, an interdisciplinary lab that integrates computing and economics to build algorithms that make people and the world better.

The full job description is here: https://www.dropbox.com/scl/fi/izvkooxmlzm44fe5u01ih/Job_Description_Predoc_Rambachan-and-Mullainathan.pdf?rlkey=nikteu91582q8leteyxome4t4&e=1&st=9rg29o01&dl=0.

REQUIRED: A minimum of a bachelor’s degree in economics, computer science, mathematics, statistics, or a related field; a minimum of two years of specialized experience with qualitative data analysis, research methods, social sciences (which may include experience gained as an undergraduate); strong analytical/coding skills; quantitative and programming skills in Python and R; and strong time and project management skills, excellent attention to detail, and strong communication skills. PREFERRED: Enthusiasm for developing or applying cutting-edge machine learning methods to understand/find solutions to real world problems.

Please apply online with a single PDF attachment titled “RA_Application_[First name]_[Last name].pdf”, including: cover letter, resume, transcript if applicable. Questions should be directed to [email protected].

Application review and interviews will be conducted in January and early February 2026. Preferred start date is June 1st, 2026, with some flexibility, and an employment term of one to two years.

11/18/2025