The M.S. in Computer Engineering at Tufts University is a 30-credit master’s program that prepares students to design and analyze the hardware, software, and networking systems that support modern computing. Students build graduate-level knowledge in areas such as computer architecture, computer networking, computer software and systems, embedded systems, security, reliability, and power-aware computing.
Jointly administered by the Department of Electrical and Computer Engineering and the Department of Computer Science, the program gives students an interdisciplinary foundation in both computing systems and engineering design. The program is offered on the Medford/Somerville campus in an on-campus format, with full-time and part-time daytime study options. Students typically complete the degree in 12 to 24 months.
The M.S. in Computer Engineering is designed for students who want advanced preparation in computing systems, hardware-software integration, networking, embedded systems, computer architecture, or related areas of electrical engineering and computer science.
The program may be a strong fit for students with academic backgrounds in computer engineering, electrical engineering, computer science, or closely related technical fields. It can support students preparing for engineering roles in industry, research and development, technology leadership, or further graduate study.
Students personalize their plan of study while building depth across the core areas of computer engineering. The program requires a minimum of 30 credits and at least 10 courses at the 100 level or above, completed with grades of Satisfactory or at least a B-. At least four lecture-based courses must be selected from the published list of computer engineering core courses, including at least one course from each of the following areas:
Coursework and research preparation may also address topics such as:
The M.S. in Computer Engineering is jointly administered by Tufts’ Department of Electrical and Computer Engineering and Department of Computer Science. This structure connects students with faculty expertise across computer architecture, computer systems, networking, embedded systems, hardware security, machine learning systems, electronic design automation, VLSI, signal processing, photonics, robotics, and emerging computing technologies.
Graduate students benefit from small classes, interdisciplinary teaching, and access to faculty whose work bridges engineering, computing, data, hardware, software, and applications in fields such as health, communications, energy, security, and intelligent systems.
The program brings together electrical and computer engineering with computer science, helping students understand how hardware, software, and networks work together in modern computing systems. This interdisciplinary structure supports students interested in both system design and real-world implementation.
Students regularly access faculty through small classes and academic advising. Faculty research areas include computer architecture, embedded systems, hardware for machine learning, hardware security, electronic design automation, VLSI systems, networking, signal processing, and emerging computing technologies.
Students can personalize their course selection while meeting core requirements in networking, architecture, and software/systems. This flexibility allows students to align the degree with interests such as hardware design, systems engineering, security, embedded computing, or research preparation.
Computer engineering at Tufts emphasizes the design and analysis of complex systems, including issues such as performance, power consumption, security, and reliability. Students gain technical preparation for engineering work that connects theory, design, implementation, and evaluation.
Graduates may pursue engineering, research, systems, hardware, or software-focused roles in areas such as computer engineering, embedded systems, computer architecture, network systems, semiconductor and chip design, cybersecurity hardware, cloud infrastructure, and research and development. Career outcomes vary based on a student’s background, focus area, thesis or non-thesis pathway, technical experience, internship or co-op experience, and professional goals.
Possible paths may include:
Computer engineering skills are relevant across computer hardware, embedded systems, networks, computing infrastructure, research, and advanced technology development.
According to the U.S. Bureau of Labor Statistics, computer hardware engineers had a median annual wage of $155,020 in May 2024, with projected employment growth of 7 percent from 2024 to 2034. Related occupation categories include computer network architects, with a median annual wage of $130,390, and computer and information research scientists, with a median annual wage of $140,910 in May 2024.
Average Salary: $138K+
Projected Job Growth (2022-2032): 5%
*Sources: Average salary and projected job growth statistics are from the U.S. Bureau of Labor Statistics Occupational Outlook Handbook.
Students in the Tufts University School of Engineering may have the opportunity to participate in the Graduate Cooperative Education Program. The co-op program allows eligible graduate students to apply classroom learning to real-world engineering projects, gain up to six months of full-time work experience, build their resumes, and strengthen their preparation for future career opportunities.
GRE General Test scores are not required for applicants who will have received a degree from a U.S. institution by the time of enrollment. GRE scores are required for all other applicants.
The School of Engineering offers partial tuition scholarships for a select group of Engineering master’s and certificate programs. When you apply for admission, you’ll automatically be considered, there’s no separate scholarship application or additional information required. Applicants are encouraged to apply early for priority scholarship consideration.
Yes. Prospective students may attend admissions events, information sessions, or campus visit opportunities to learn more about Tufts graduate programs and the application process. Visit go.tufts.edu/gradevents for the event schedule and previously recorded videos.
Applicants can apply online through Tufts Graduate Admissions Portal. Required materials typically include transcripts, a resume or CV, letters of recommendation, and a statement of purpose. International applicants may also need to submit English proficiency documentation. Visit the admissions page for current deadlines and application requirements.
At Tufts University, we believe every qualified applicant deserves the opportunity to pursue graduate study. We are dedicated to helping you understand your financial options and to ensuring that graduate education at Tufts is both accessible and within reach.
Tuition costs for this graduate program are billed at a per credit rate:
| Estimated Tuition for MS Program | |
|---|---|
| Tuition* | $1,799 per credit |
| Total Credits Required | 30 |
| Enrollment Status | Full-Time: 3-4 courses per semester (9-12 credits) Part-Time: 1-2 courses per semester (3-6 credits) |
| Estimated Tuition per Semester | Full-Time: $16,191 - $21,588 per semester (9-12 credits) Part-Time: $5,397 - $10,794 per semester (3-6 credits) |
| Estimated Total Tuition* | $53,970 |
*Estimated based on 2025-2026 tuition rates. Rates are subject to change each academic year. For further information about the full cost of attendance, including additional fees and estimated indirect costs (housing, transportation, etc.), please visit Student Financial Services.
The Tufts University School of Engineering offers partial, merit-based tuition scholarships for the majority of our graduate and certificate programs. All applicants are automatically considered for these awards as part of our holistic admissions review process—no separate scholarship application or additional materials are required.
Additional funding opportunities may include Tufts Double Jumbo Scholarships for Tufts graduates, Bridge Program Scholarships for students and alumni from select partner institutions, and veteran and military education benefits for eligible service members and their dependents, including participation in the Yellow Ribbon Program.
To further support your investment in a Tufts graduate education, a range of financing options are available, including federal and private student loans. For more details, please visit our Graduate Financial Aid page.
Research/Areas of Interest: Machine Learning for Systems Biology; Metabolic Engineering, computer-aided design for integrated circuits
Research/Areas of Interest: computer architecture, computer systems, power-aware computing, embedded systems, mobile computing, computer systems for machine learning, workload characterization, quantum computing, learning sciences and computer systems for human subjects research
Research/Areas of Interest: data science, software systems engineering, performance analysis, system, network, and data management
Research/Areas of Interest: computational molecular biology, data science, graph algorithms, network science, discrete mathematics
Research/Areas of Interest: emerging technologies, non-volatile memories, SoC design, hardware for machine learning, noise modeling and reliability
Research/Areas of Interest: design of silicon-based mixed-mode VLSI systems (analog, digital, RF, optical), analog signal processing, and optoelectronic system-on-chip modeling and integration for applications in optical wireless communication and biomedical imaging
Research/Areas of Interest: trusted AI, hardware security, electronic design automation, VLSI architectures for machine learning and emerging cryptographic systems, and AI for healthcare and biomedical applications.
Research/Areas of Interest: Scientific machine learning: physics-informed ML, representation learning, generative modeling, interpretability; Complex systems: nonlinear dynamics, chaos, interacting quantum systems, materials science, fluid turbulence Website: https://petery.lu
Research/Areas of Interest: nanophotonics, optical beam shaping, neuroengineering, chip-scale imaging and microscopy, quantum information systems Research Website: https://sites.tufts.edu/amohanty/
Research/Areas of Interest: Signal processing; image processing; simulation modeling
Research/Areas of Interest: (opto)electronics and photonics, compound semiconductors, emerging materials, epitaxial growth, hetero- and nano-structures, applications in sensing, integrated photonics, and quantum information systems