APPLICATION DEADLINE: January 25, 2019, 11:59 PM ET
The National Library of Medicine Associate Fellowship is a one-year residency program for recent library science graduates interested in a career in health sciences librarianship. The program combines curriculum and project work and is located at the National Library of Medicine on the campus of the National Institutes of Health in Bethesda, Maryland.
The Associate Fellowship provides knowledge and skills in project work ranging from:
- Fundamentals of data science, and projects in data wrangling, data analysis, data visualization, programming, and data policy
- Creation of online tutorials and educational videos, conducting user needs assessments
- Development of an in-depth understanding of the development, production, implementation of NLM product and services
The Associate Fellowship offers opportunities for professional development through:
- Participation in lectures, exercises, conferences, short and extended visits to other health sciences libraries
- Workshops on work style, resume review, negotiation, and presentation skills
- Mentorship from a program coordinator and NLM staff who serve as preceptors
The participant will receive an annual stipend of $56,233; additional $6,000 supplement for health insurance; relocation funding; and travel and training support to attend conferences.
- Master’s degree in an ALA-accredited library/information science program, earned by August of the year of appointment or within the previous two years. (Undergraduate degree can be in any major.)
- Opportunity open to U.S. and Canadian citizens only. Note: Canadians with ALA-accredited Master’s degrees should use the same application process as U.S. citizens. U.S. citizens will receive first preference.
- Work experience in a library or health sciences environment.
For a full description of this opportunity and to submit your application, visit https://www.zintellect.com/Opportunity/Details/NIH-NLM-2018-01
If you have any questions, please send an email to email@example.com