University of Michigan

What you'll study

The PhD emphasises original research supported by advanced coursework across mechatronics, robotics and automation. Students typically take modules covering topics such as advanced dynamics and robot kinematics, nonlinear and optimal control, perception and computer vision, machine learning for robotics, sensor fusion, embedded real-time systems, motion planning, human-robot interaction, and formal methods for autonomous systems. Coursework is combined with intensive laboratory work in experimental platforms (mobile robots, manipulators, aerial systems), sensor and actuator integration, and simulation and software frameworks.

Programme structure usually includes initial coursework to build breadth and depth, qualifying or preliminary examinations to confirm research readiness, identification of a supervisory committee and advisor, and sustained dissertation research leading to a doctoral thesis. Students are expected to contribute to peer-reviewed publications, present at conferences, and participate in collaborative projects with other departments (for example electrical engineering, mechanical engineering, computer science, aerospace engineering, and biomedical engineering) and cross-disciplinary centres.

Entry requirements

• Academic background: A relevant master's degree is typical but exceptional candidates with a strong bachelor's degree in mechanical engineering, electrical engineering, computer science, robotics, mechatronics or a closely related field are also considered.
• Prerequisite knowledge: Solid grounding in mathematics (linear algebra, probability, optimisation), systems and control theory, programming (C/C++, Python, ROS), and signals and systems or equivalent coursework or experience.
• Application materials: A detailed CV, statement of research interests outlining proposed directions and faculty fit, academic transcripts, and letters of recommendation are required. Evidence of prior research experience (publications, technical reports or project portfolios) strengthens an application.
• English language: Applicants whose primary language is not English must meet institutional English-proficiency requirements.
• Research fit: Admission is heavily influenced by alignment between the applicant's research interests and available faculty supervisors; contacting potential advisors prior to application is recommended.

Career prospects

Graduates move into a wide range of technical and leadership roles. Common career destinations include tenure-track academic positions and postdoctoral research, R&D roles in robotics and automation companies (industrial automation, automotive and autonomous systems, aerospace, medical robotics, field and service robots), research labs at technology firms, government and national research laboratories, and founding or technical leadership roles in start-ups. Graduates are also sought after for systems and controls engineering roles, advanced software engineering for autonomy, and specialised positions in perception, machine learning and human-robot interaction.

Why study at University of Michigan

• Interdisciplinary ecosystem: The University of Michigan provides strong cross-departmental collaboration between mechanical engineering, electrical and computer engineering, computer science and related units, enabling broad technical exposure and joint research projects.
• Research centres and facilities: Students have access to dedicated robotics labs, advanced fabrication and prototyping facilities, and shared computational and experimental resources that support both hardware and software research.
• Faculty expertise: A large faculty body with expertise across core and emerging areas of robotics and automation offers a variety of potential advisors and research directions, from fundamental theory to system integration and applied development.
• Industry engagement and career support: Strong connections with industry partners, technology transfer offices and entrepreneurship resources help students translate research into real-world applications and explore commercial pathways.
• Ann Arbor and campus life: The broader campus and regional innovation ecosystem provide additional opportunities for collaboration, internships and professional development in a vibrant academic community.