University of Michigan

What you'll study

The Master's in Computer Engineering at the University of Michigan covers both the physical and algorithmic layers of modern computing systems. Students study microelectronic circuits and VLSI design alongside computer architecture, embedded systems, and the software stacks that run on them. The curriculum supports customisation through elective courses, project work and research opportunities.

Typical core and elective topics

• Digital and analogue integrated circuit design — transistor-level design, timing, power and layout considerations for chips.
• Computer architecture — processor design, memory systems, cache coherency, multi-core and many-core architectures.
• Embedded systems and real-time computing — hardware-software co-design, sensors and actuators, RTOS concepts.
• Hardware description and verification — HDL modelling (e.g. Verilog/VHDL), simulation, formal and dynamic verification techniques.
• Systems and software — compilers, operating systems, concurrency, and performance optimisation for hardware platforms.
• Interfacing with AI and machine learning — accelerated neural network inference, hardware-software partitioning for ML workloads.
• Advanced topics and electives — emerging areas such as photonics, quantum-aware hardware, security for hardware, and semiconductor process considerations.

Programme structure

Students typically complete a combination of required coursework and electives, along with a substantial culminating experience. Options generally include a thesis track, a project or research practicum, and a course-only route for students focused on industry entry. Lab courses and group design projects give hands-on experience with chip design tools, FPGAs, board-level prototyping and system integration.

Entry requirements

Applicants are normally expected to hold a relevant bachelor’s degree in electrical engineering, computer engineering, computer science or a closely related field. A strong foundation in mathematics, signals/systems, digital logic and programming is required. Typical admissions documents include academic transcripts, letters of recommendation, a statement of purpose, and a CV.

Where applicable, applicants whose first language is not English will need to demonstrate proficiency via an accepted English language test. Relevant professional experience, research experience, or coursework in core engineering subjects can strengthen an application. Admissions decisions consider the overall academic record, fit with faculty research areas or departmental specialisms, and the applicant’s technical preparation.

Career prospects

Graduates of the programme move into roles spanning both hardware and software domains. Common career paths include:

• Design engineer roles in semiconductor companies (ASIC/FPGA design, physical design, verification).
• Systems engineer roles developing embedded platforms for automotive, aerospace, robotics, medical devices and IoT.
• Computer architect and performance engineer positions in companies building servers, mobile processors and accelerators.
• Roles at hardware-enabled AI companies, working on accelerators, inference optimisation and hardware-software co-design for ML.
• Technical positions in verification, test and manufacturing or design automation (EDA) tool development.
• Research or further study leading to doctoral programmes and academic careers.

Alumni typically find opportunities in technology companies, startups, research laboratories and government or defence contractors, as well as continuing into interdisciplinary teams that bridge electronics, software and data science.

Why study at University of Michigan

The University of Michigan has a long-established engineering faculty and a broad ecosystem that supports computer engineering study. Students benefit from access to specialised research laboratories, cleanrooms and prototyping facilities, as well as collaborations across departments such as computer science, robotics, and materials science. Strong industry links in the region and beyond facilitate internships, sponsored projects and employment connections.

The programme emphasises hands-on, project-based learning and gives students the opportunity to work with faculty on cutting-edge research in areas such as low-power design, computer architecture, embedded intelligence and hardware security. In addition, the university’s interdisciplinary culture and entrepreneurial support systems help students translate technical work into practical products and startups.