Position Description: Professor Gabriel Kreindler is seeking a predoctoral fellow. The fellow will work on projects in the areas of urban, spatial and development economics, which involve structural modeling and estimation and large-scale randomized experiments.
This position will last for one year, from July 2025 until June 2026. The fellow will be an active participant in the Harvard research community and will have opportunities to develop their own research agenda. The fellowship may lead to co-authoring papers with the PI.More information on Professor Kreindler can be found at this link: https://sites.google.com/site/gabrielkreindler
Responsibilities will include: • Designing, writing, and fine-tuning code for structural model simulation, with a focus on computational performance. Most of the code will use the Julia programming language • Non-linear estimation and other statistical analyses • Running power calculations for randomized controlled trials using structural models • Assisting in the preparation of academic journal submissions and code and data for publication • Literature reviews
*The position is fully paid, and a visa can be arranged.
Basic Qualifications: Candidates for this position must have a bachelor's degree in a quantitative field such as economics, computer science, mathematics, statistics, physics, etc. Strong programming and mathematical skills required. Knowledge of the Julia programming language is not required. Experience writing highperformance code is strongly preferred, and this can take various forms: working with large model simulations or large data, compiled programming languages, algorithms, etc. The position is an especially good match for candidates contemplating application to a PhD program in economics or another quantitative field.
Special Instructions: Please include contact information for three references in your cover letter.
Applications will be accepted and reviewed on a rolling basis. Highly qualified applicants will be invited to complete a coding task and for an interview.
Contact Information: Shree Manari
Contact Email:
econacademicappointments@fas.harvard.edu
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.
Supplemental Questions: Required fields are indicated with an asterisk (*).