Carnegie Mellon University

Overview

The Ph.D. in Business Technologies at Carnegie Mellon University is an advanced program dedicated to exploring the economics and quantitative evaluation of cutting-edge technologies. This doctoral program emphasizes emerging fields such as artificial intelligence, machine learning, digital platforms, and blockchain systems. Students engage in collaborative research with faculty, focusing on the intersection of technology design and tangible business outcomes.

What you'll study

The curriculum is structured to provide a solid foundation in economic principles and quantitative research methods, tailored for technology-focused scholarship.

• Core coursework: Students will complete essential classes in economics, innovation, and empirical research methods relevant to technology.
• AI/ML and computational methods: Training in machine learning and artificial intelligence equips students to conduct innovative, data-driven research.
• Cross-department coursework: Students have the opportunity to enroll in additional technology-related courses across campus, particularly those offered by the School of Computer Science, depending on their research focus.
• Research progression: Participants will develop a dissertation topic, refine their research questions, and meet program milestones as outlined by the Ph.D. regulations.
• Dissertation: Students will complete an original research dissertation that makes a significant contribution to the field of emerging technologies.

Entry requirements

Admission to the program is competitive and typically requires a robust academic background in a quantitative discipline, such as economics, computer science, statistics, or operations research. While specific thresholds for GPA, GRE, or GMAT scores may not be consistently published, prospective applicants should review the official admission guidance for the most current information.

Career prospects

Graduates of the Ph.D. in Business Technologies are well-prepared for a variety of advanced career paths. They can pursue roles in academia, research institutions, or industries that leverage technology for economic development. Potential career outcomes include positions as data scientists, technology consultants, academic researchers, or policy advisors, where they can apply their expertise in analyzing and implementing emerging technological solutions.