Job Listings

Pre-Doctoral Fellowship (Prof Dell)

Company:
Harvard University
Job Location:
Cambridge, 02138
Category:
Economics
Type:
Full-Time

School: Faculty of Arts and Sciences

Position Description

Professor Melissa Dell is seeking a predoctoral fellow. This position will be for one year, from July 2024 until June 2025. The fellow will be an active participant in the Harvard research community and will have opportunities to co-author papers with the PI and develop their own research agenda. More information on Professor Dell can be found at this link:

https://dell-research-harvard.github.io/

Responsibilities will include:
  • Training and fine-tuning deep learning-based models, drawing from computer vision, natural¬† language processing, and graph neural networks
  • ¬†Preparing transparent, interactive data visualizations
  • Conducting statistical analyses
  • Literature reviews
  • Assisting in the preparation of academic papers being submitted to journals
  • Preparing code and data for publication
The position is fully paid, and a visa can be arranged.

Basic Qualifications

Candidates for this position must have a bachelor's degree in economics, statistics, mathematics, computer science, physics, or another quantitative field. Experience with deep learning or econometrics is not required, but knowledge of Python is strongly preferred. 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 interview.

Contact Information

Shree M

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.
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