Computer Engineering graduates earn a median $94,408 Across 176 US programmes, two years after finishing
See the degree grade →The Master of Science in Computer Engineering at the University of Texas develops advanced skills in hardware and software integration, embedded systems, digital design and computer architecture. It suits graduates with a background in electrical engineering, computer science or related fields who want to pursue technical leadership, research roles or specialised engineering positions in industry or academia.
The programme combines core topics in computer engineering with elective options that let you specialise. Typical coursework covers digital systems and computer architecture, embedded systems, VLSI design, real-time and operating systems, computer networks, and advanced topics in hardware-software co-design. Students also study applied mathematics for engineers, signal processing fundamentals relevant to hardware design, and verification and testing methods.
Applicants are normally expected to hold a recognised bachelor’s degree in electrical engineering, computer engineering, computer science or a closely related discipline. Strong quantitative preparation—courses in calculus, linear algebra and programming—is required. Relevant professional experience or prior research can strengthen an application for candidates with non-traditional backgrounds.
Graduates are prepared for roles that bridge hardware and software, including embedded systems engineer, FPGA/ASIC design engineer, systems architect, firmware developer, and hardware verification engineer. Career paths extend to telecommunications, semiconductor industry, automotive and aerospace systems, consumer electronics, robotics, and IoT companies. Those interested in research or teaching may continue to doctoral study or join research laboratories in industry or government.
The University of Texas offers extensive research facilities, well-equipped electronics and systems laboratories, and faculty active in areas such as computer architecture, embedded systems, hardware security and machine learning for edge devices. The programme emphasises close faculty supervision, opportunities for interdisciplinary collaboration, and project work with industry partners. Students benefit from a broad alumni network and connections to regional technology companies, which support internships and employment opportunities.
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