Carnegie Mellon University

PhD Program in Machine Learning

Carnegie Mellon University's doctoral program in Machine Learning is designed to train students to become tomorrow's leaders through a combination of interdisciplinary coursework, hands-on applications, and cutting-edge research. Graduates of the Ph.D. program in Machine Learning will be uniquely positioned to pioneer new developments in the field, and to be leaders in both industry and academia.

Understanding the most effective ways of using the vast amounts of data that are now being stored is a significant challenge to society, and therefore to science and technology, as it seeks to obtain a return on the huge investment that is being made in computerization and data collection. Advances in the development of automated techniques for data analysis and decision making requires interdisciplinary work in areas such as machine learning algorithms and foundations, statistics, complexity theory, optimization, data mining, etc.

The Ph.D. Program in Machine Learning is for students who are interested in research in Machine Learning. For questions and concerns, please contact us.

The PhD program is a full-time in-person committment and is not offered on-line or part-time.

Requirements for the PhD in Machine Learning

  • Completion of required courses, (6 Core Courses + 1 Elective)
  • Mastery of proficiencies in Teaching and Presentation skills.
  • Successful defense of a Ph.D. thesis.

Ph.D. students are required to serve as Teaching Assistants for two semesters in Machine Learning courses (10-xxx), beginning in their second year. This fulfills their Teaching Skills requirement.

Conference Presentation Skills
During their second or third year, Ph.D. students must give a talk at least 30 minutes long, and invite members of the Speaking Skills committee to attend and evaluate it.

It is expected that all Ph.D. students engage in active research from their first semester. Moreover, advisor selection occurs in the first month of entering the Ph.D. program, with the option to change at a later time. Roughly half of a student's time should be allocated to research and lab work, and half to courses until these are completed.

Master of Science in Machine Learning Research - along the way to your PhD Degree.

Other Requirements
In addition, students must follow all university policies and procedures.

Rules for the MLD PhD Thesis Committee (applicable to all ML PhDs):
The committee should be assembled by the student and their advisor, and approved by the PhD Program Director(s).  It must include:

  • At least one MLD Core Faculty member
  • At least one additional MLD Core or Affiliated Faculty member
  • At least one External Member, usually meaning external to CMU
  • A total of at least four members, including the advisor who is the committee chair
It will be our responsibility, not yours, to worry about your tuition and stipend while you are in our program.  We are committed to providing your full tuition and stipend support for the coming academic year.  We intend to continue this support as long as you continue to make satisfactory progress in our program.  Students who do not have external financial support will be funded via graduate assistantships, awarded for a nine-month period from September to May, which would normally come from their advisor’s grants.  Because of that, specific research opportunities may be constrained by funding availability.  Students who have partial external financial support will be supplemented to bring them to the full level of support, and often receive an additional supplement on top of that.  If you have dependents, we will also pay you a dependency allowance that is 10% of the MLD monthly base stipend per eligible dependent, unless you have a spouse or qualifying domestic partner who earns more than $500 per month.

Application Information

For applicants applying in Fall 2024 for a start date of August 2025 in the Machine Learning PhD program, GRE Scores are STRONGLY RECOMMENDED.
The committee uses GRE scores to gauge quantitative skills, and to a lesser extent, also verbal skills.

Proof of English Language Proficiency
If you will be studying on an F-1 or J-1 visa, and English is not a native language for you (native language…meaning spoken at home and from birth), we are required to formally evaluate your English proficiency.

We require applicants who will be studying on an F-1 or J-1 visa, and for whom English is not a native language, to demonstrate English proficiency via one of these standardized tests: TOEFL (preferred), IELTS, or Duolingo.  We discourage the use of the "TOEFL ITP Plus for China," since speaking is not scored.

We do not issue waivers for non-native speakers of English.  In particular, we do not issue waivers based on previous study at a U.S. high school, college, or university.  We also do not issue waivers based on previous study at an English-language high school, college, or university outside of the United States.  No amount of educational experience in English, regardless of which country it occurred in, will result in a test waiver.

Submit valid, recent scores:  If as described above you are required to submit proof of English proficiency, your TOEFL, IELTS or Duolingo test scores will be considered valid as follows:

If you have not received a bachelor’s degree in the U.S., you will need to submit an English proficiency score no older than two years. (scores from exams taken before Sept. 1, 2023, will not be accepted.)

If you are currently working on or have received a bachelor's and/or a master's degree in the U.S., you may submit an expired test score up to five years old. (scores from exams taken before Sept. 1, 2019, will not be accepted.)

Additional details about English proficiency requirements are provided on the FAQ page.