Job Information
Harvard University Pre-Doctoral Fellowship (Prof Dell) in Cambridge, Massachusetts
Details
Title Pre-Doctoral Fellowship (Prof Dell)
School Faculty of Arts and Sciences
Department/Area
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.
Additional Qualifications
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.
Minimum Number of References Required
Maximum Number of References Allowed
Keywords
Supplemental Questions