Carnegie Mellon University

M.S. in Automated Science

Ray and Stephanie Lane Computational Biology Department


M.S. in Automated Science Admissions 

The Master of Science in Automated Science: Biological Experimentation program uses the School of Computer Science online application for admissions. Students are admitted for the fall semester and cannot begin in the spring.



In addition to the Rales and GEM fellowships, a limited number of Director's fellowships are available for U.S. citizens or permanent residents of underprivileged socioeconomic background. To be considered for one of these fellowships, please complete the fellowship application form by TBD

You must submit the following with your application:

  • If your native language is not English, then you must submit a TOEFL, unless you completed your undergraduate degree in the United States. A successful applicant will normally have a total TOEFL iBT score of at least 100.
  • A PDF of your most recent transcript from each college and/or university you attended, even if no degree was granted.
  • Your resume in PDF format.
  • Your Statement of Purpose — In addition to research interests, experience, and objectives, candidates are invited to include an optional paragraph describing contributions to outreach efforts and/or promoting diversity, equity, and inclusion.
  • Three letters of recommendation, at least two of which are from faculty or recent employers.

Note When submitting your application, you may be asked to enter the date you expect to take the GRE.  If this happens, just enter any date in the future. We ignore that field because GREs are not required for admission.

For more on the application process, please refer to the SCS Online Graduate Application Instructions.

You may also be interested in CMU’s MS in Computational Biology degree program. It shares some training faculty and three required courses with MSAS, but the intellectual content is distinct. The MSCB program offers broad training in advanced biological and data science concepts encompassing genomics, biological modeling and simulation, and machine learning. In contrast, The MSAS curriculum combines cutting edge artificial intelligence and laboratory automation to enable students to become leaders in the emerging field of automated science. Both programs prepare students for jobs in industry or additional graduate study in competitive PhD programs.

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