Pre-Doctoral Fellowship (Prof Dell) at Harvard University in Cambridge, Massachusetts

Job Description:

Harvard University


Title: Pre-Doctoral Fellowship (Prof Dell)

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.




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

PI239889891

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