Archives Intern (Part-Time)
The American Museum of Natural History is one of the world's preeminent scientific and cultural institutions, and has as its mission to discover, interpret, and disseminate information about human cultures, the natural world, and the universe through a wide-ranging program of scientific research, education, and exhibition.
The department of Vertebrate Paleontology, in the Museum's Division of Paleontology, is seeking a part-time Archives Intern, responsible for working with and supporting the Project Archivist in compiling and accessing the Frick Collections, weeding materials, and supporting efforts in conservation and digitization. They will participate in discussions of their findings in weekly status meetings.
This position is expected to work one day per week for approximately 7 hours.
Job duties include, but are not limited to:
- Provide support in processing the Vertebrate Paleontology archives associated with the Frick Collections, including:
- Assess and analyze unprocessed materials.
- Select and document materials for future conservation.
- Assist in surveying, analyzing, and processing materials.
- Digitize materials.
- Assist with other duties relevant to the project's focus.
The expected salary range for the Archives Intern is $27/hour - $31/hour. This position is overtime-eligible.
Pay will be determined based on several factors. The hiring range for the position at commencement is based on the type of work and the scope of responsibilities. The salary and placement offered is based on a number of individualized factors, including, but not limited to, skills, knowledge, training, education, credentials, areas of specialization, and depth and scope of experience.
Required Qualifications:
Preferred Qualifications:
- ALA-accredited master's degree in library and information science, or current enrollment in an ALA-accredited master's program in library and information science.
- Archival processing in a museum or academic setting.
- Experience with using AI tools to digest large datasets.
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