Rochester Institute of Technology

What you'll study

The PhD programme emphasises original research in computer engineering and closely related areas of electrical engineering. Students follow a curriculum that combines advanced coursework, qualifying examinations, and an extended dissertation project under the supervision of a faculty advisor. Core topical areas include embedded systems and real-time computing, computer architecture and VLSI, digital and mixed-signal design, systems-on-chip, hardware security, networking and communications, high-performance computing, machine learning for systems, and cyber-physical systems.

Typical coursework covers advanced topics such as:

• Advanced Digital Design and VLSI
• Computer Architecture and Parallel Systems
• Embedded Systems Design and Real-Time Systems
• Advanced Signal Processing and Communications
• Hardware Security and Trust
• Machine Learning for Systems
• Research Methods and Experimental Design
• Seminars in Current Research Topics

Early in the programme students complete required and elective graduate courses to build breadth; they then pass a qualifying or comprehensive examination to advance to candidacy. The principal component is an independent dissertation that contributes new knowledge to the field, typically demonstrated through peer-reviewed publications and a public defence. Students also gain experience in grant writing, teaching, and research collaboration.

Entry requirements

Applicants are normally expected to hold a relevant master’s degree or the US equivalent in electrical engineering, computer engineering, computer science, or a closely related discipline. A strong academic record and demonstrable preparation for research are required, including coursework in areas such as digital systems, signals and systems, programming, and mathematics (linear algebra, probability, calculus).

Application materials typically include:

• Official academic transcripts
• A curriculum vitae or résumé detailing research and technical experience
• A statement of purpose describing research interests and potential faculty matches
• Letters of recommendation from academic or professional referees
• Examples of prior research (publications, technical reports, or project summaries) where available

International applicants must demonstrate English proficiency through recognised tests or exemptions where applicable. Admission decisions also consider fit with faculty research interests and availability of faculty supervisors and funding support. Some programmes may request GRE scores, though requirements can vary; check the department for current guidance.

Career prospects

Graduates of the PhD in Electrical and Computer Engineering pursue careers across academia, industry, and government. Common career paths include tenure-track faculty positions, research scientist or R&D engineer roles in technology companies, senior engineering and architecture roles in hardware and systems firms, and technical leadership in startups. Other opportunities include positions in national laboratories, defence and space organisations, semiconductor and fabrication industries, network and communications companies, and specialised consulting.

PhD holders are often prepared for roles that require deep technical expertise, independent research skills, and experience leading cross-disciplinary teams. The programme’s emphasis on publication, collaboration and applied projects also supports transitions into industry research labs and entrepreneurial ventures.

Why study at Rochester Institute of Technology

Rochester Institute of Technology combines strong technical departments with hands-on research facilities and a collaborative, interdisciplinary culture. The computer and electrical engineering faculty engage in applied and theoretical research across microelectronics, systems, networking, security and machine learning, providing a broad range of possible dissertation topics and industry-relevant projects.

The university offers access to modern laboratories, specialised cleanroom and prototyping facilities through campus centres, and substantial computational resources for simulation and machine learning. RIT’s focus on experiential learning, established industry partnerships, and a supportive graduate community help students develop both research depth and practical skills. Funding opportunities such as research assistantships and fellowships are commonly available for qualified doctoral students, enabling focused progress on their research agendas under close faculty mentorship.