The HKU CDS Research Internship 2026 gives undergraduate students the chance to spend their summer conducting research at the University of Hong Kong’s School of Computing and Data Science. Through this program, participants work alongside faculty members on real academic projects and experience what postgraduate research at HKU looks like in practice.
Students are matched with supervisors according to their interests and must present their research outcomes once the internship concludes.
Program Overview
- Location: Hong Kong
- Host: University of Hong Kong – School of Computing and Data Science
- Length: Roughly seven weeks
- Expected schedule: mid-July to late August 2026
- Intake: About 40 international undergraduate students
Funding Support
Selected interns normally receive:
- A total stipend of about HK$19,601
- Financial support intended for accommodation, travel, meals, and daily expenses
Academic Areas
Projects are available for students in:
- Computer Science and software-related fields
- Artificial Intelligence or Data Science
- Statistics, actuarial science, or similar technical areas
Who Can Apply?
Eligible candidates are typically:
- Undergraduate students in Year 2 or Year 3
- Enrolled in computing or quantitative programs
- Academically strong and interested in research
- Available for the full internship duration
Application Requirements
Applicants usually need:
- Resume or CV
- Academic transcript
- Motivation statement
- Letter confirming support from their university
- Optional reference letter
How to Apply
Students should review research groups, choose preferred areas, complete the online form, and submit documents. Offers are generally based on supervisor selection and academic fit.
Deadline
Applications normally close at the end of May each year (check the official page for updates).
Why This Internship Matters
The HKU CDS internship combines international exposure, faculty mentorship, and real research experience. It’s especially valuable for students planning graduate study abroad or careers in computing and data science.
