Georgia Institute of Technology

What you'll study

This PhD programme is research-intensive and combines advanced coursework with an extended original research project leading to a dissertation. Typical taught topics you will study include dynamics and control of robotic systems, sensor fusion and perception, machine learning for autonomy, embedded and real‑time systems, mechatronic design, human–robot interaction, planning and optimisation, and systems engineering for automation.

• Core technical areas: nonlinear and optimal control, multibody dynamics, kinematics, sensors and actuators, and real‑time embedded computing.
• Perception and intelligence: computer vision, probabilistic state estimation, deep learning for robotics and decision‑making under uncertainty.
• Systems and applications: industrial automation, mobile and legged robotics, aerial systems, surgical and assistive robotics, and autonomous vehicles.
• Research methods and professional skills: experimental methods, simulation and validation, research ethics, scientific communication and grant writing.

The programme typically requires completion of advanced graduate coursework to establish breadth and depth, passing of a qualifying or candidacy examination, preparation and defence of a research proposal, and completion and public defence of a doctoral dissertation. Students work closely with a faculty advisor and often participate in multidisciplinary research centres and labs, combining hardware prototyping, software development and theory.

Entry requirements

Applicants are normally expected to hold a relevant master's degree or equivalent in engineering, computer science, robotics, applied mathematics or a closely related discipline, with strong academic performance. Exceptional candidates with a bachelor’s degree and outstanding preparation may also be considered.

• Academic record: graduate transcripts demonstrating strong performance in relevant undergraduate and graduate coursework (control theory, dynamics, programming, signals and systems, or equivalent).
• Research potential: evidence of research experience such as a thesis, publications, project reports or substantial industry R&D work.
• Supporting documents: a curriculum vitae, a statement of research interests, and at least three academic or professional letters of recommendation.
• English language: international applicants whose first language is not English will be required to demonstrate English proficiency according to institutional policy.
• Additional assessments: some applicants may be asked for a portfolio of projects, code samples, or to attend an interview; standardised test requirements vary and should be checked on the department admissions page.

Career prospects

Graduates from this field move into a broad range of roles across academia, industry and government. Common career paths include positions as university faculty and postdoctoral researchers, senior research scientists and engineers in robotics, autonomy and artificial intelligence teams, and technical leads for automation and control in manufacturing and aerospace.

• R&D roles in robotics and automation companies, startups and large technology firms developing perception, planning and control systems.
• Systems engineering, integration and product development in industrial automation, medical devices, defence and automotive sectors.
• Leadership roles in national laboratories, research institutes and public-sector technology programmes.
• Entrepreneurship and technology transfer, launching startups or commercialising robotics innovations.

Why study at Georgia Institute of Technology

Georgia Tech is a highly interdisciplinary research university with strong, long‑standing programmes in robotics, controls and mechatronics. The institute provides access to specialised research centres and laboratories that foster collaboration across mechanical engineering, electrical and computer engineering, computer science and biomedical engineering.

• Research environment: students benefit from faculty expertise across theoretical and experimental robotics, and from labs equipped for hardware prototyping, field testing and large‑scale system demonstration.
• Industry and regional ecosystem: located in a major technology and manufacturing hub, the institute has extensive partnerships and collaborative opportunities with industry, government laboratories and startups.
• Interdisciplinary opportunities: the programme encourages collaboration with complementary research areas such as machine learning, human factors, advanced manufacturing and materials science.
• Professional development: doctoral students receive mentoring in research, teaching and entrepreneurship, positioning graduates for influential careers in research, industry leadership and academia.

Prospective applicants should consult the department and graduate school pages for detailed application procedures and any programme‑specific guidance.