Carnegie Mellon University


Master of Science in Computational Biology
The M.S. in Computational Biology program enrolls students who desire a more immediate career in industry or who wish to explore computational biology without committing to a doctoral program. It also draws returning professionals who seek to enhance their skills and practices in this new interdisciplinary field.
MD/Ph.D. in Computational Biology
The Medical Scientist Training Program (MSTP) seeks to train talented students to become physician-scientists in an environment that integrates superlative medical education and customized graduate work in biomedical research.
Ph.D. Program in Computational Biology
An interdisciplinary graduate training program in computational biology that brings together the world-class strengths of Carnegie Mellon and the University of Pittsburgh in computer science and biomedical research, and enables outstanding students to receive unique training that will place them among the leaders of this field.


Computer Science—M.S.
The Master of Science program in Computer Science offers students with a Bachelor's degree the opportunity to improve their training with advanced study in Computer Science. We cater to students with basic analytic skills and a strong aptitude for mathematics, programming, and logical reasoning. An undergraduate degree in computer science is not required.
Center for the Neural Basis of Cognition Training Program: An Option for Computer Science Graduate Students
The Center for the Neural Basis of Cognition Training Program is an interdisciplinary graduate training program operated jointly by Carnegie Mellon University and the University of Pittsburgh. Affiliated departments include Computer Science, Robotics, Machine Learning, Psychology, Statistics, and Biomedical Engineering at Carnegie Mellon, and Neuroscience, Neurobiology, Psychology, Mathematics, and BioEngineering at the University of Pittsburgh. The CNBC program is designed to allow students to combine intensive training in a "home" department with broad exposure to other disciplines that touch on neural computation and problems of higher brain function.
Computer Science—Ph.D.
This program is for those who wish to pursue an academic or research career in computer science. Students take courses and conduct applied and theoretical research in algorithms and complexity, artificial intelligence, hardware and software systems, and programming languages. Within our collaborative, hands-on and highly interdisciplinary research environment, students have a supreme opportunity to push the frontiers of computing. A dual degree Pittsburgh-Portugal PhD program in Computer Science is also offered.
Doctoral Program in Algorithms, Combinatorics and Optimization
This unique interdisciplinary doctoral program in Algorithms, Combinatorics and Optimization draws on Carnegie Mellon's strengths in all three areas. It is sponsored jointly by the Tepper School of Business (Operations Research group), the School of Computer Science (Algorithms and Complexity group) and the Mathematics Department (Discrete Mathematics group). The program brings together the study of the mathematical structure of discrete objects and the design and analysis of algorithms in areas such as Graph Theory, Combinatorial Optimization, Integer Programming, Polyhedral Theory, Computational Algebra, Geometry and Number Theory. This integration of the study of structure and its uses in computation theory is a central theme of the program. The Ph.D. in Computer Science also offers a minor in ACO for those students who wish to have a formal involvement with the ACO program but still receive a Ph.D. in Computer Science. Please visit the ACO program for additional information.
Doctoral Program in Pure and Applied Logic
Carnegie Mellon's Doctoral Program in Pure and Applied Logic is an interdisciplinary venture jointly sponsored by the Department of Mathematics, the Department of Philosophy, and the Department of Computer Science. Carnegie Mellon has a large and active group of faculty whose research and teaching interests span all aspects of logic, with a particularly strong concentration in foundational aspects of computing. This Logic Community has an established record of collaborations in pursuing theoretical research, conducting major implementation projects, and running colloquia and workshops.
Dual PhD Programs CMU-Portugal in Computer Science
The Department of Computer Science (CSD) of the School of Computer Science at Carnegie Mellon University offers a dual degree Ph.D. program in Computer Science in cooperation with several Portuguese universities. This Ph.D. program is part of the activities of the Information and Communication Technologies Institute (ICTI), resulting from a Portugal-CMU partnership agreement.


Master of Entertainment Technology [with CFA]—M.E.T.
The two-year M.E.T. is jointly conferred by the College of Fine Arts and School of Computer Science. The concept behind both the Entertainment Technology Center and the M.E.T. is having technologists and fine artists work together on projects that produce artifacts intended to entertain, inform, inspire or otherwise affect an audience/guest/player/participant. We do not turn artists into technologists, or vice-versa. While some students will be able to achieve mastery in both areas, it is not our intent to have our students master “the other side.” Instead, we intend for a typical student in the program to enter with mastery or training in a specific area and spend his or her time at Carnegie Mellon learning the vocabulary, values and working patterns of the other culture.


Human-Computer Interaction—Master of
This one-year interdisciplinary professional degree prepares students to become leaders in the design and implementation of software systems that can be used easily, effectively and enjoyably. Students will learn techniques for identifying needs for software systems, design principles that make systems visually clear and appealing, and techniques for building systems and evaluating their effects on people and organizations. This program is offered in both Pittsburgh and Portugal.

Educational Technology and Applied Learning Sciences — Master in (METALS)
This one-year interdisciplinary professional masters, jointly taught by the Human Computer Interaction Institute and the Psychology Department,  trains students to design, develop and evaluate evidenced-based programs for learning in settings that range from schools to homes, workplaces to museums, and online to offline learning environments.  Graduates will challenge the future of learning by re-examining the goals of education and assessment.  Graduates are prepared to take key positions in corporations, universities and schools as designers, developers, and evaluators of educational technologies as well as learning engineers, curriculum developers, learning technology policy-makers, and even chief learning officers. Students with backgrounds in psychology, education, computer science, design, information technology, or business are encouraged to apply.

Human-Computer Interaction—Ph.D.
This highly interdisciplinary program considers the aspects of computer science, behavioral sciences and design that come together to form the discipline of human-computer interaction. Reflecting the diversity of its faculty, and their interests in the intersection of people and computing, the program prepares students to become world-class HCI researchers through a diverse set of classroom, research and teaching experiences.


Software Engineering Distance Education
Since 1996, the Software Engineering Program has offered graduate courses that develop skills in the fundamentals of software engineering, with an emphasis on design, analysis and management of large-scale software systems, via distance education. The curriculum, which is the same as the campus MSIT-SE Program, emphasizes practical results, teaches effective methods to solve problems, and evaluates solutions based on sound engineering practices. The program is ideal for software development professionals who need to acquire in-depth and advanced knowledge of emerging technologies.

Master of Science in Information Technology–Software Engineering (MSIT-SE)
The Master of Science in Information Technology – Software Engineering (MSIT-SE) degree is designed for early-career professionals with less than two years of work experience. The program shares the same core courses as the MSE program, and results in a final real-world capstone project. Considerably smaller than the MSE Studio in scope and size, the MSIT-SE Practicum affords the student an opportunity to demonstrate what has been learned in the core and elective courses through its practical application in a realistic project setting. The typical applicant has an undergraduate degree in Computer Science or other scientific or technical discipline, one to two years of industry experience, and has worked on at least one notable project.

Master of Science in Information Technology (MSIT) in eBusiness Technology
An increasing portion of all business is being conducted over the Internet.  Building eBusiness systems requires application of technology to real commercial situations. The eBusiness Technology program is not lecture-based, but consists of 16 real-world team projects in eBusiness consulting in which students must solve realistic problems incorporating a spectrum of current eBusiness issues. The final 9 weeks of the program are spent working on actual projects contributed by industrial sponsors. By that time, students have not only absorbed new technologies, but have acquired job-critical skills such as time management, team organization and the ability to produce professional work product and deliver effective and persuasive presentations.

Master of Science in Information Technology - Embedded Software Systems (MSIT-ESE)
The Master of Science in Information Technology – Embedded Software Engineering (MSIT-ESE) is a professional master’s degree program drawing from the combined resources and strengths of the School of Computer Science's Institute for Software Research (ISR) and the Department of Electrical and Computer Engineering (ECE). The professionally-oriented degree provides the foundations and skills in computer science, hardware and electrical engineering, and systems engineering necessary for effective embedded software engineering.  The use of an application-based capstone Practicum project is a central component in the curriculum, and is particularly appropriate for students who intend to return to industry after receiving their degree.

Master of Science in Information Technology - Software Engineering Management (MSIT-SEM)
A collaborative effort between Carnegie Mellon’s Heinz School of Public Policy and Management, the School of Computer Science, and the Software Engineering Institute, the MSIT-SEM is designed for mid-level managers currently working in information technology or software development positions who are eager to increase the breadth and depth of their knowledge. Applicants to the program are inclined to be those who strive to direct within software development organizations, or in the broader business sector that effectively acquires, integrates, and manages software. The program is ideal for working information technology managers, and is designed to be completed in three years of part-time study. Delivered mostly via distance education, the program culminates in a real-world capstone project.

Master of Science in the field of Information Technology in Privacy Engineering (MSIT-PE)
The Master of Science in Information Technology—Privacy Engineering (MSIT-PE) degree is a one-year program designed for computer scientists and engineers who wish to pursue careers as privacy engineers or technical privacy managers. Designed in close collaboration with industry and government, this program is intended for students who aspire to play a critical role in building privacy into future products, services, and processes.

Master of Software Engineering (MSE)
The MSE program is designed for practicing software developers who have at least two years of experience and want to become technical leaders. You’ll learn how to apply current best practices while adding value by effectively managing large, diverse teams and complex projects.
Master of Business Administration and Master of Software Engineering (MBA/MSE)
The Master of Business Administration and Master of Software Engineering dual-degree is offered by Carnegie Mellon’s School of Computer Science and the Tepper School of Business. It is a full-time campus program, consisting of six academic semesters and a required internship in the summer of the first year.

Master of Information Technology Strategy (MITS)
The Master of Information Technology Strategy (MITS) is a cooperative endeavor of the College of Engineering, School of Computer Science (SCS) and the Institute for Politics and Strategy.  The MITS program provides a multidisciplinary education that prepares students to define and conceptualize:
  • the emerging environment of threats caused by cyber operations;
  • opportunities for enhanced information analysis and exploitation;
  • development and management of innovative information technology systems; and
  • decision-making challenges associated with the above.
The program has four areas of concentration: Data Analytics, Politics and Strategy, Information Security, Software and Networked Systems.
Master of Software Engineering/ Master of Business Administration [with Tepper]—(MBA/MSE)
The Master of Business Administration and Master of Software Engineering (MBA/MSE) is a six-semester program that starts each year in August. The focus of the dual-degree program is to develop the technical and the managerial skills needed for software design, development, engineering and implementation. This dual-degree program is designed for exceptionally strong candidates for either the MBA or the MSE programs. Each applicant must have engineering/science backgrounds, and must apply and be admitted to both the MBA and the MSE programs. Candidates must take both the Graduate Management Admissions Test and the Graduate Record Examination. The completion date cannot be accelerated; students must remain in residence at Carnegie Mellon for the seven semesters of the program.

Certificate in Software Engineering (CSE)
The Certificate in Software Engineering (CSE) provides the individual with the body of knowledge (BOK) that has enduring value in software engineering. It provides the individual with knowledge that enables them to understand critical concepts when dealing with complex software projects.
Societal Computing —Ph.D.
The Ph.D program in Societal Computing prepares students to be tomorrow’s leaders in designing, constructing and assessing technology that will transform society, business, policy, and law or be used to computationally reason about these complex socio-computational transformations.  Application areas include: privacy, dynamic social networks, link analysis, team and organizational performance, computer simulation, bio-surveillance, sustainability, electronic voting, and supply chain management, socio-technical ecosystems, and product development ecosystems.
Software Engineering—Ph.D.
The Ph.D. program in software engineering prepares students for academic and industry leadership positions in software engineering. Software has become an essential building material in nearly all sectors of the economy.  Students build on experience in both research and in practice to identify and address the core challenges of software engineering practice. These challenges relate to diverse topics such as software architecture and design, software assurance and program analysis, measurement and tools, teams and organizations, end-user programming, and other topics. This degree is offered in both Pittsburgh and Portugal.
Software Engineering - [Dual program with Portugal] - Ph.D. 
The Institute for Software Research (ISR) in the School of Computer Science at Carnegie Mellon University offers a dual degree PhD program in Software Engineering in cooperation with several Portuguese universities. This PhD program is part of the activities of the Information and Communication Technologies Institute (ICTI), resulting from a Portugal-Carnegie Mellon partnership agreement.


Master of Computational Data Science (MCDS)
The MCDS degree focuses on engineering and deploying large-scale information systems. Our comprehensive curriculum equips you with the skills and knowledge to develop the layers of technology involved in the next generation of massive information system deployments and analyze the data these systems generate. When you graduate, you’ll have a unified vision of these systems from your core courses; internship experience; and semester-long, group-oriented capstone project. MCDS graduates are sought-after software engineers, data scientists and project managers at leading information technology, software services and social media companies.
Language Technologies—M.S.
The MLT program prepares students for a research career in academia or industry. In this program, you’ll be immersed in research for two full years. During the academic year, your time will be evenly split between taking courses and doing research with your faculty advisor. Your summer will be devoted entirely to research. Many MLT grads continue on to Ph.D. programs at CMU and other top institutions, while others pursue careers at companies emphasizing research and rapid innovation.
Master of Science in Intelligent Information Systems (MIIS)
The MIIS degree focuses on recognizing and extracting meaning from text, spoken language and video. As an MIIS student, you’ll receive the department’s deepest exposure to content analysis and machine learning. In addition to completing the program’s coursework, you’ll work on directed study projects with your faculty advisor for two semesters; participate in a summer internship; and collaborate with your peers on a semester-long, group-oriented capstone project. This combination of classroom instruction, professional experience, and using new skills in significant projects with world-class colleagues will help prepare you for a successful career in industry or government.
Language and Information Technology - Ph.D.
The Ph.D. in LTI focuses on developing the next generation of scientific and entrepreneurial leaders. The first two years of the Ph.D. program are similar to our MLT program. After the second year, you will spend most of your time working closely with your faculty advisor on research that advances the state-of-the-art in computer science.
Ph.D. students are expected to publish papers about original research in the most competitive scientific journals and international conference proceedings, and to present their research at conferences and workshops. Most of our Ph.D. graduates become professors and research scientists, while a few have started their own companies.
Language and Information Technologies— Dual-Degree Ph.D. [Portugal partnership]
The LTI offers a dual-degree Ph.D. in Language and Information Technologies in cooperation with the Universidade Nova de Lisboa and the Instituto Superior Técnico at the Universidade Tecnica de Lisboa. Students jointly enrolled in the LTI Ph.D program spend a year in Lisbon, then two years at Carnegie Mellon taking classes in linguistics, computer science, statistical learning and task orientation.  After completing the majority of their academic requirements, students return to Portugal for the next two years to conduct extensive research, ultimately leading to a dissertation topic that will be publicly defended. One adviser from each institution co-supervises their student’s progress and helps to define their final thesis topic.


Machine Learning—M.S.
Students who are already in a Ph.D. program at Carnegie Mellon may apply for a secondary master’s in data mining. This program will build on Carnegie Mellon’s Machine Learning Department, which has assembled a multidisciplinary team of faculty and students across several academic departments, dedicated to producing the next generation of data mining methods.
Master of Science in Machine Learning
This highly selective program consists primarily of coursework, with a very limited research component, and typically takes three semesters to complete. Students in this program take the same set of core courses as students receiving a PhD in Machine Learning, and also complete a Data Analysis Project. Some students may require an additional semester to fill in gaps in their undergraduate training.
5th Yr. Masters in Machine Learning
The 5th Year Masters in Machine Learning allows Carnegie Mellon undergraduates to earn a MS degree in one additional year by taking some of the required ML courses as an undergraduate.
Secondary Masters in Machine Learning
This program is designed for (and only open to) current Carnegie Mellon PhD students who wish to obtain a Master of Science in Machine Learning concurrently with their PhD. The program is also open to Carnegie Mellon faculty and staff.
Machine Learning—Ph.D.
The Ph.D. program in Machine Learning is designed to give students a deep understanding of the computational and statistical principles that underlie learning processes, an exposure to real-world applications of machine learning, and an opportunity to design novel machine learning algorithms that advance the state of the art. Our graduates have already gone on to take faculty positions in top-ranked Computer Science departments, Statistics departments, and Engineering departments at other universities, as well as positions in major industrial research laboratories.
Machine Learning/Neural Basis of Cognition—Ph.D.
Students participate in the Center for the Neural Basis of Cognition’s graduate training program, an interdisciplinary add-on program affiliated with eight Ph.D. programs at Carnegie Mellon and the University of Pittsburgh that focuses on how the brain gives rise to the mind. Students study neurophysiology, systems neuroscience, cognitive neuroscience and computational modeling.
Machine Learning & Public Policy Joint Ph.D.
Many recent developments in the fields of machine learning and public policy suggest significant potential for increased collaboration between these fields. The Joint Ph.D. Program in Machine Learning and Public Policy is a new program for students to gain the skills necessary to develop new state-of-the-art machine learning technologies and apply these successfully to real-world policy issues.
Statistics and Machine Learning Joint Ph.D.
Exciting research is being done at the boundary between machine learning and statistics. This is reflected at Carnegie Mellon by the strong ties between Carnegie Mellon’s Machine Learning Department and the Department of Statistics. This new joint program is aimed at preparing students for academic careers in both computer science and statistics departments at top universities. Students in this track will be involved in courses and research from both the Department of Statistics and the Machine Learning Department. During the first two years, the emphasis is on course work, with students situated in Statistics. During the following years, the student will be located in the Machine Learning Department.


A master’s degree in robotics requires both understanding a range of technical fields and having experience with synthesizing real systems. The curriculum, designed primarily for a two-year course of study, reflects both the breadth and the hands-on nature of robotics, covering core topics including perception, cognition, action and mathematical foundations. This degree is designed both as a professional, terminal degree and as an introduction to research for those who want to consider the Ph.D.
Computer Vision (MSCV) - M.S.
Computer vision is the study of acquiring and interpreting visual imagery. As the technology matures, its applications in industry continue to expand exponentially in areas of great commercial value.  The goals of the 16 month (three semesters plus summer) MSCV program are to provide a robust set of courses encompassing current and emerging state of the art computer vision topics that will prepare students for careers in this field, and to facilitate hands-on experience on real research and development projects addressing current applications.
Robotic Systems Development - M.S.
The Master of Science (M.Sc.) Degree in Robotic Systems Development (MRSD) is an advanced graduate degree with a combined technical/business focus for recent-graduates / practicing-professionals already engaged in, or wishing to enter, the robotics and automation field as practitioners in the commercial sector. This Masters degree program distinguishes itself from any other offered program by teaching the multidisciplinary know-how and skills needed to succeed in today’s industry. The MRSD curriculum provides a broad education in the sciences and technologies of robotics, while reinforcing theory through hands-on laboratory projects and exposing students to practical business principles and skills. This unique hands-on curriculum allows students to work on team-oriented and practical system-level robotics development and integration projects. Key business concepts and practices in the curriculum include technology planning, product conceptualization and development, team management, project management, prototyping, production, marketing, and sales.
Ph.D. research runs the course from foundations to applications. Our fundamental work includes new approaches to sensor and motor technology, foundations of machine perception, motion planning, algorithms, computer graphics, robot learning, speech recognition and many others. Application areas include autonomous highway vehicles, space exploration and factory automation. The program brings research areas together that would otherwise be spread among separate departments or even separate universities. Our curriculum is tuned to the needs of robotics, defining an intellectual focus and commitment to robotics. Students in the program are building a new discipline by formulating the ideas and building the systems that will determine our basic understanding of robots and of purposeful behavior in general. A well-prepared student can complete the doctorate in four to five years.
Robotics/Neural Basis of Cognition - Ph.D.
Students participate in the Center for the Neural Basis of Cognition’s graduate training program, an interdisciplinary add-on program affiliated with eight Ph.D. programs at Carnegie Mellon and the University of Pittsburgh that focuses on how the brain gives rise to the mind. Students study neurophysiology, systems neuroscience, cognitive neuroscience and computational modeling.