Digital Humanities Fellowship in Analysis of Historical Documents

The Smithsonian Institution Data Science Lab (datascience.si.edu), housed within the Office of the Chief Information Officer, in collaboration with the United States Holocaust Memorial Museum, is seeking to support a graduate student or postdoctoral fellow to lead a project to improve the discoverability of the United States Holocaust Memorial Museum digitized collections with the use of machine learning tools. We are particularly interested in applying deep learning techniques to classify unknown document types and natural language processing techniques to delve into document contents, with all project components  leading to interactive visualizations of results. The scope, however, can be molded to fit the fellow’s interests. The successful applicant will have the opportunity to become a certified Carpentries instructor and teach data science skills as part of our training program for Smithsonian staff, fellows, and interns (https://datascience.si.edu/carpentries) if desired. 

The Data Science Lab was formed in response to the dramatic increase in all forms of digital data across the Smithsonian (19 museums, 9 research centers, and zoo). We seek to build collaborations both across Smithsonian units, as well as universities and other institutions.

Members of our group work on a variety of data-intensive research topics including biodiversity genomics and machine learning applications of digitized museum collections. 

Given the interdisciplinary nature of the project, postdoctoral applicants should possess a PhD with a relevant interdisciplinary focus. This may include either social sciences and humanities disciplines (e.g., history, sociology, Judaic studies) with a research focus in digital data or technical disciplines (e.g., computer science, NLP) with a research focus on historical document analysis. Applicants should demonstrate a strong publication record and the ability to conduct independent research. Potential graduate student fellows should be enrolled in a graduate program in a relevant field of study at a degree-granting institution. Strong written and communication skills are also required. Applicants should be proficient in Python and familiar with deep learning libraries such as PyTorch or TensorFlow. The fellow will be advised by both Smithsonian and USHMM staff with expertise in the technical and historical subject matter, respectively. 

Appointment is initially for one year, with the possibility for renewal based on performance. Due to COVID-19 restrictions, the Data Science Lab is working remotely for the foreseeable future. Applicants are not required to relocate to the Washington, DC area. Stipend is $60,000 per year for postdoctoral fellows and $36,000 per year for graduate student fellows, each with an additional $5,000 health insurance offset. Start date is flexible.

To apply, submit a curriculum vitae, a 1-page statement of research interests, and contact details for 2-3 academic references to Rebecca Dikow (DikowR@si.edu). Review of applications will begin July 27th, 2020 and continue until the position is filled.