Department/Area: The Institute for Quantitative Social Science
This posting is for a data science fellow in deep learning. The fellow will work with the PI, Professor Melissa Dell, to develop document layout analysis methods that will be used to create a digital database of the contents of historical newspapers across thousands of American communities. The fellow will be an active participant in the Harvard research community and will have opportunities to develop their own research agenda. The fellowship will offer opportunities to coauthor publications and conference submissions.
The project will develop deep learning-based document layout analysis methods to convert image scans from over 7,000 American community newspapers in all 50 states, encompassing over 12 million newspaper editions published over a period spanning more than a century, into digitized text. The resulting publicly available American Communities Computable Newspaper Database will substantially enhance and democratize access to historical newspaper content.
The position requires a thorough knowledge of deep learning methods. An ideal candidate will have a background in document layout analysis. The position requires a bachelor's degree. The fellow must be self-directed and able to apply the relevant research frontiers to this use case. The ideal candidate will be planning to apply to PhD programs in computer science or electrical engineering and would benefit from spending time working in a university setting.
The position has an eight-month term (with a potential opportunity for extension, conditional on funding availability and performance). The desired term start and end dates are September 1, 2020 – April 30, 2021, adjustable based on hire date and the current grant end date of 6/30/21.
Thorough knowledge of deep learning methods required.
Background in document layout analysis required
A Bachelors degree is required.
The Fellow must be self-directed and able to apply the relevant research frontiers to this use case.
The ideal candidate will have a strong background in document layout analysis.
The ideal candidate will be planning to apply to PhD programs in computer science or electrical engineering and would benefit from spending time working in a university setting.
PLEASE DO NOTAPPLYONLINE. Interested candidates should send a CV and one page research statement detailing your experience with deep learning based methods to [email protected]
Only applicants who follow these instructions will be considered.
IQSS sits in the Division of Social Science, which is strongly committed to creating and supporting a diverse workforce. Respect and fairness, kindness and collegiality, and trust and transparency are among the values we espouse and promote in our workplace culture. We work hard to ensure a healthy, inclusive and positive environment where everyone does their best work in support of Harvard's mission.
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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.
Internal Number: 9744
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