PhD in Robotics

PhDDoctoralRobotics

About This Programme

A University-funded (Year 1, pending a faculty advisor match) PhD in Robotics: motion planning, multi-robot systems and humanoid robotics research with a 32-credit thesis.

Course Highlights

  • Ph.D. students are centrally funded by MBZUAI in Year 1 while matching with a faculty advisor, then funded by that advisor from Year 2, subject to a confirmed match and satisfactory progress.
  • Research in perception, human-robot interaction, swarm intelligence and autonomous systems.
  • Access to computing labs with nearly 1,000 Nvidia DGZ-1/2 GPU servers.
  • Qualifying and Candidacy exams then a 32-credit thesis.

What You'll Study

A 3–4 year full-time doctoral programme on the Masdar City campus with advanced robotics cores, electives, research methods and an internship, a Qualifying Exam (Year 1) and Candidacy Exam (Year 2), then an original 32-credit thesis. Ph.D. students are centrally funded by MBZUAI in Year 1 while matching with a faculty advisor, then move to that advisor's funding from Year 2, subject to a confirmed match and satisfactory progress.

Core courses

Core: 4 courses, 16 credit hours, taken by every student. The published study plan writes the summer internship as INT799; the core-course and internship panels both give INT899, the doctoral code, which is stored here.

  • Advanced Robotic Motion Planning (ROB801)4 credits
  • Advanced Topics in Robotics: Multi-robot Systems (ROB802)4 credits
  • Advanced Humanoid Robotics (ROB803)4 credits
  • Vision for Autonomous Robotics (ROB804)4 credits

Research methods, internship and thesis

  • Advanced Research Methods (RES899)2 credits
  • Ph.D. Internship (up to four months) (INT899)2 credits
  • Robotics Ph.D. Research Thesis (ROB899)32 credits

Elective courses

Students select a minimum of two elective courses totalling 8 credit hours.

Published elective list

  • Single Cell Biology and Bioinformatics (CBIO8101)4 credits
  • Advanced Foundations of AI System Design (CS8201)4 credits
  • Advanced Computer Vision (CV801)4 credits
  • Advanced 3D Computer Vision (CV802)4 credits
  • 3D Geometry Processing (CV804)4 credits
  • Life-long Learning Agents for Vision (CV805)4 credits
  • Advanced Topics in Vision and Language (CV806)4 credits
  • Advanced Topics in Reinforcement Learning (ML806)4 credits
  • Causality and Machine Learning (ML808)4 credits
  • Advanced Learning Theory (ML809)4 credits
  • Dimensionality Reduction and Manifold Learning (ML813)4 credits
  • Advanced Parallel and Distributed Machine Learning Systems (ML815)4 credits
  • Emerging Topics in Trustworthy ML (ML818)4 credits
  • Foundations of Machine Learning (ML8101)2 credits
  • Advanced Machine Learning (ML8102)2 credits
  • Probabilistic Graphical Models (ML8503)2 credits
  • Collaborative Learning (ML8509)4 credits
  • Natural Language Processing - Ph.D. (NLP805)4 credits
  • Advanced Natural Language Processing - Ph.D. (NLP806)4 credits
  • Speech Processing - Ph.D. (NLP807)4 credits
  • Current Topics in Natural Language Processing (NLP808)4 credits
  • Advanced Speech Processing (NLP809)4 credits
  • Vision-to-Language Generation (NLP8501)2 credits

Entry Requirements

Academic: A bachelor's degree with CGPA 3.5/4.0 or a master's with CGPA 3.0/4.0 in a STEM field.
English: IELTS Academic 6.5, TOEFL iBT 90, PTE Academic 60, Cambridge C1 Advanced 180, Cambridge C2 Proficiency 200, or Duolingo English Test 120. MBZUAI does not publish an EmSAT route.

Three references and an independent research statement. Screening exam and technical interview.

Careers

Graduates pursue robotics and autonomous-systems research and faculty roles across academia and industry.

Accreditation & Professional Recognition

Accredited by the UAE Commission for Academic Accreditation (status Active on the CAA register).

Programme Details

Award

Doctor of Philosophy (PhD) in Robotics

Start Date

Annual Fall intake (August)

Typical Offer

Bachelor's CGPA 3.5 or master's 3.0 (STEM); IELTS 6.5 / TOEFL 90

Duration

4 years

Qualification

Doctorate

Subject Area

Robotics

Study Pattern

Full time

Delivery Format

In person

Related Programmes in Robotics