The Smithsonian Institution Data Science Lab housed within the Office of the Chief Information Officer (SI-OCIO), in collaboration with the National Gallery of Art (NGA), is looking to fill a pre/postdoctoral fellowship in Washington, DC.
The Data Science Lab was formed in 2016 in response to the dramatic increase in all forms of digital data across the Smithsonian (19 museums, 9 research centers, and National Zoo). The Lab seeks to build collaborations between Smithsonian, universities, and other cultural and educational 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.
Inspired by the Metropolitan Museum of Art’s Collection Metadata Project and the Art Genome Project, this Smithsonian-NGA collaboration seeks to support either a graduate student or postdoctoral fellow to explore and experiment with the National Gallery of Art’s high-resolution images and data records. Competitive candidates might work on a variety of projects, including (but not limited to) expanding descriptive metadata of the Gallery’s collection through machine learning, exploring the Gallery’s data through the development of new UI/UXs, or other similar endeavors as designed by the fellow and the host institutions. Projects with a public-facing focus or with potential future scholarly and educational use are especially welcome.
The resources of the NGA will be at the disposal of the fellow, including over 90,000 high resolution images of the collection as well as data records for the objects represented by those images. The fellow will also have access to vast research files, conservation imagery, and scholarly expertise. The fellow will be provided with a dedicated technical point of contact at the NGA to initiate, facilitate, and help coordinate activities at the NGA in support of the project. The fellow will collaborate with the NGA’s imaging specialists, collection management specialists, curators, researchers, archivists, librarians, and data architects. The fellow will become part of the Smithsonian OCIO Data Science Lab (comprised of data scientists, postdoctoral fellows, predoctoral fellows, and interns) and have access to Smithsonian computational resources including Smithsonain High-Performance Computing Cluster to complete the project.
Given the interdisciplinary nature of the project, postdoctoral applicants should possess a Ph.D./Graduate degree with a relevant focus and knowledge of cultural heritage data best practices and standards. Applicants should also demonstrate a strong publication record and the ability to conduct independent research. Potential graduate student fellows must be enrolled in a graduate program in a relevant field of study at a degree-granting institution. 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 NGA staff with expertise in the technical and subject matter, respectively. Strong written and communication skills are essential.
Appointment is for one year, with the possibility for renewal for another year based on performance. The stipend is $60,000 per year for postdoctoral fellows and $40,000 per year for graduate student fellows, with an additional $5,000 health insurance offset. Due to COVID-19 restrictions, the Data Science Lab and most NGA staff are still working remotely although a return to on-site is possible in Fall 2021. Applicants are not required to relocate to the Washington, DC area. The start date and work location are flexible and will be negotiated with the fellow.
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). Application review will begin on September 15th, 2021, and continue on a rolling basis until the position is filled.
