Skip to main content

Digital Humanities Postdoctoral Fellowships

The Smithsonian Institution Data Science Lab (datascience.si.edu) housed within the Office of the Chief Information Officer (SI-OCIO) in Washington, DC, is seeking a postdoctoral fellow to conduct independent research and digital humanities scholarship in collaboration with the United States Holocaust Memorial Museum.

The Data Science Lab was recently formed in response to the dramatic increase in all forms of digital data across the Smithsonian (19 museums, 9 research centers, and a 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.

Collaboration with the United States Holocaust Memorial Museum (USHMM):

We are seeking a 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.

Applicant Requirements:

Given the interdisciplinary nature of this project, 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with a research focus in digital data or technical disciplines (e.g., computer science, NLP) with a research focus on historical document analysis.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. Strong written and communication skills are also required. Applicants should be proficient in Python, familiar with machine learning frameworks such as PyTorch or TensorFlow, and have experience with a High-performance Computing Cluster. 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. Stipend is $60,000 per year, with an additional $5,000 health insurance offset. Please contact Rebecca Dikow at DikowR@si.edu with questions. To apply, submit a curriculum vitae, a 1-page statement of research interests, and contact details for 2-3 academic references to SI-DataScience@si.edu.

Back to Top
Error | Smithsonian Data Science Lab

Error

The website encountered an unexpected error. Please try again later.