Job Summary
The Center for Strategic and International Studies’ International Security Program (ISP) seeks two highly motivated candidates for a full-time (35 hours per week), three-month (with the possibility of extension to six-month) internship beginning in April 2023. This will be an in-person position located at our DC office.
The interns will conduct research and administrative tasks to support projects on the future of warfare, strategic competition, and great power competition. Candidates should have an interest in data science, emerging technologies, and strategic studies.
Interns should expect to be an active participant in conducting research, writing commentaries and reports, facilitating crisis simulations and wargames, and conducting quantitative and qualitative data analysis. This position requires an ability to manage multiple priorities simultaneously and have a strong, independent work ethic. Most importantly, we are interested in any candidate who is passionate about our research, willing to learn new skills, and strives to contribute and implement new ideas.
The intern will be paid an hourly rate of $16.10–18.10, commensurate with experience.
Essential duties and responsibilities
• Contribute to written products by conducting background research, writing drafts of commentaries and reports, copy-editing, and editing citation.
• Assist with the logistical preparation and design of wargames, tabletop exercises, and crisis simulations.
• Assist with event preparation and staffing for both public and private events.
• Attend meetings and events to take notes on various topics.
• Perform other duties as necessary in support of staff members.
Knowledge, education, and experience
• Currently enrolled in a bachelor’s, master’s, or PhD program.
• 0-2 years of relevant work experience (including internships).
• Excellent written communication skills, including the ability to write academic papers (5-15 pages), copyedit, and complete citations.
• General knowledge of strategic studies and international relations theory.
• Background using data science platforms like R and Python desirable, but not required.