Pre-Doctoral Fellowship (Prof Dell)

Harvard University, United States

Updated: 1 day ago
Location: Cambridge, MASSACHUSETTS
Deadline: ;

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 [email protected]
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
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