* The Lab cannot provide a response without the required documents listed below.
1. Research Areas:
- AI-driven or digital history, digital East Asian studies (e.g. digital Korean studies)
- Cold War history, including North Korean history, the history of socialism and authoritarianism
- STEM (Science, Technology, Environment, Medicine) history, including energy history
2. Lab Activities:
- Conduct innovative research in history using rare archives and digital analytics
- Collect, process, utilize, and vectorize rare historical data from archives overseas (works in 2024)
3. Eligibility Criteria:
- Students versed in employing digital analytics, with a strong interest in history or relevant disciplines (e.g. history of science or STS)
- Diligent and well-rounded personality
4. Process:
- Send an email to dhwoo1234@kaist.ac.kr (Subject: [Master's Program]_Your Name or [Ph.D. Program]_Your Name) with the following documents:
4-1. Required Attachments:
- Self-introduction and research proposal (or at least a few concrete research ideas or items)
- CV (or resume) and academic transcripts plus standardized English test scoresÂ
- Description of machine learning skills & experience
4-2. Research Proposal:
- The more detailed, the better. Present a clear vision on how you plan to combine your interests and skills to make an academic contribution through your research
- Mention at least three (3) researchers and explain how their scholarship will be referenced or incorporated into your study
- Include at least three (3) SCI-, SSCI-, or A&HCI-indexed, English-language journals where you intend to submit your future work
5. Next Steps:
- Successful applicants will be contacted for interviews after document review
Join us to explore the intersection of digital technology and historical research!
Some benefits include, but are not limited to:
Full tuition fees provided;
Stipend and scholarship opportunities;
Participation in vibrant R&D projects;
Design your own research under co-guidance with capable KAIST faculty members;
Hands-on experience of convergence studies.