The PhD in Machine Learning is an interdisciplinary doctoral program spanning three colleges (Computing, Engineering, Sciences). Students are admitted through one of eight participating home schools:
- Computer Science (Computing)
- Computational Science and Engineering (Computing)
- Interactive Computing (Computing) – see Computer Science
- Aerospace Engineering (Engineering)
- Biomedical Engineering (Engineering)
- Electrical and Computer Engineering (Engineering)
- Industrial Systems Engineering (Engineering)
- Mathematics (Sciences)
External applications are only accepted for the Fall semester each year. The application deadline varies by home school with the earliest deadline of December 1. Most home schools have a final deadline of December 15. Check with home schools above for more specific details.
Applicants must meet all admissions standards (including requirements on the minimum GPA, minimum GRE/TOEFL scores) of the home unit, which may vary. After an initial review, the unit’s representative of the ML Ph.D. Faculty Advisory Committee (FAC) will submit their candidates for review and the final admission decision will be made by the ML FAC.
The committee’s decision to admit will be based on (1) prior academic performance of the applicant in a B.S. or M.S. program at a recognized institution, including coursework and independent research projects, (2) prior work experience relevant to ML, (3) the applicant’s statement of purpose, and (4) the letters of support.
Please note that application requirements may vary by home unit, including the application deadlines and test score requirements, as well as support for incoming students (including guarantees of teaching assistantships and/or fellowships) are determined by the home units. Please review the home unit links above or contact them directly for details.
Please contact home units directly for questions related to:
- Application deadlines
- Assistantship/fellowship opportunities
- Program fit
- GRE and TOEFL requirements
- Desired content in Statement of Purpose and Recommendation Letters
- Other academic program specific information
For technical application questions, please contact firstname.lastname@example.org:
- Creating or using an account login
- Application fee waiver
- Forgotten password
- Uploading documents
- Difficulty with recommender emails
- How to access application status information (including application checklist)
- Difficulty with the touchnet payment system
Georgia Tech Transfer Students
If you are already enrolled in a Ph.D. program in one of the eight participating schools noted above, you may apply to the ML Ph.D. program as a transfer student. You will be subject to the standard ML curriculum and qualifying requirements, so this is recommended only for graduate students in their first or second year.
Potential transfer students will need to have found a thesis advisor who is willing to support them on a research assistantship. For more information, please email the ML Academic Advisor, Stephanie Niebuhr at email@example.com