Pre-Doctoral Fellowship at Harvard University in Cambridge, Massachusetts

Job Description:

Harvard University


Title: Pre-Doctoral Fellowship

School: Faculty of Arts and Sciences

Department_Area: Salata Institute

Position Description: The Salata Institute for Climate and Sustainability at Harvard University is recruiting its inaugural cohort of Predoctoral Fellows to support the research of affiliated faculty. The Salata Institute draws from expertise across the University to pursue real-world solutions to address the climate crisis.

Fellows will be given one-year appointment beginning in the summer of 2025 with the possibility of renewal for a second year upon mutual agreement. Each fellow will work with 1-2 faculty mentors on research projects that cover a broad range of environmental economics topics and methods. Faculty mentors for this program will include Ishan Nath, Anna Russo, Wolfram Schlenker, and Charles Taylor.

This is a one year term position beginning September 2025 with the possibility of renewal.


Position Description

An important goal of the fellowship is to prepare fellows for doctoral research in environmental economics or related fields. Fellows will be exposed to a range of research tasks, including:

Writing code to clean, process, visualize, and analyze data.

Assisting with estimating structural models.

Conducting literature reviews.

Producing figures, tables, and slides for presentations and working papers.

Faculty mentors are committed to the mentorship and professional development of the fellows and to fostering a supportive, collaborative, and fun research environment.

Fellows will be expected to work full-time, in-person at Harvard in Cambridge, Massachusetts, where they are encouraged to attend events and seminars and take courses (in the Economics department or at the Harvard Kennedy School). Fellows will receive an annual salary of $60,000 and benefits.

Applicants should hold or plan to receive an undergraduate degree by the summer of 2025.

Basic Qualifications: Candidates must meet the following basic qualifications to be considered for this role: Anticipated bachelor's degree by summer 2025 and a strong quantitative background in economics, math, statistics, and/or computer science

Additional Qualifications: Experience with programming, data science, and geospatial analysis (especially R, Stata, Julia, MATLAB , or Python).

An enthusiasm for empirical research and an interest in pursuing a PhD in economics or related fields (e.g., public policy).

An ability to work independently and with attention to detail.

Effective communication skills and an ability to work in a collaborative environment.

Special Instructions: Please upload a CV; transcript; one letter of recommendation; and a one-page statement describing your research and programming experience and interests. Candidates who advance to a second round will be invited to complete a programming test and participate in a Skype interview. Applicants will be accepted on a rolling basis until the position is filled.

We will be filling three positions for the same role.

Interested candidates should submit a letter of interest (under one page), including a reference to specific topics, fields, or methods of interest and a resume/CV.

Candidates who advance to later stages of the process may also be asked to complete a coding exercise and provide contact information for a reference who can speak to their research skills and interests.

This position will have a 3-month orientation and review period.

The health of our workforce is a priority for Harvard University. With that in mind, we strongly encourage all employees to be up to date on CDC -recommended vaccines.

Contact Information: Zoe Stone

Contact Email: zoe_stone@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.

Minimum Number of References Required: 1

Maximum Number of References Allowed: 1


Supplemental Questions: Required fields are indicated with an asterisk (*).

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