| Course Level: | Doctorate | |
|---|---|---|
| Course Duration: | 2 Years | |
| Course Language | English | |
| Required Degree | Master’s Degree | |
| First Year Total Fees: | $ 7200(₹ 560000) | |
| Total Course Fees: | $ 14400(₹ 1120000) | |
Choosing a PhD in Machine Learning at Jeju National University (Ara Campus), South Korea, offers a unique blend of cutting-edge research and a supportive academic environment. The university emphasizes innovative AI and ML applications, providing access to advanced labs, high-performance computing resources, and interdisciplinary collaboration. Students benefit from expert faculty guidance, participation in international conferences, and opportunities to publish in top-tier journals. Jeju’s vibrant campus life, cultural diversity, and natural beauty create an inspiring setting for research and personal growth. This program equips scholars with the skills and experience to become leaders in AI, data science, and machine learning globally.
Category |
Details |
|---|---|
|
Program Name |
PhD in Machine Learning |
|
Degree Awarded |
Doctor of Philosophy (PhD) |
|
Course Duration |
4–5 years (full-time) |
|
Language of Instruction |
English / Korean (depending on courses) |
|
Yearly Tuition Fees |
4,500,000 – 6,000,000 (~$3,500 – $4,700 USD) |
|
Total Tuition Fees |
18,000,000 – 30,000,000 (~$14,000 – $23,500 USD) |
|
Total Program Cost |
Including living expenses: ~$25,000 – $40,000 USD over 4–5 years |
|
Eligibility |
Master’s degree in Computer Science, Data Science, AI, or related field; strong math/statistics background |
|
Admission Requirements |
Academic transcripts, CV, research proposal, recommendation letters, English proficiency (TOEFL/IELTS) if applicable |
|
Application Intake |
Fall intake (September); some programs may allow Spring intake |
|
Scholarship |
University scholarships, research assistantships, government scholarships (KRW 800,000–1,000,000/month) |
|
Career Prospects |
AI/ML researcher, data scientist, academic professor, software engineer, R&D positions in global tech companies |
|
Curriculum Structure |
Core ML courses, advanced AI electives, research seminars, thesis research, teaching practice, dissertation defense |
