Program Overview

Master of Science in Robotics

The Master of Science in Robotics is a research-based degree that aims to develop students' interest in, knowledge, and understanding of robotics and autonomous systems. The program prepares students for Ph.D. research in the area and/or the industry workforce.

Overview

The program teaches students to apply research techniques and knowledge gained to solve complex problems in the field of Robotics. Robotics research and the development of intelligent systems continue to be one of the key priorities set by both government and industry. Interdisciplinary in scope, the Master's in Robotics provides an ideal foundation for what today's experts in robotics and intelligent systems need to know.

Program Details

• Mode: Full-time
• Credits: 36
• Location: On campus

Program Learning Outcomes

The program learning outcomes (PLOs) are aligned with the Emirates Qualifications Framework and are divided into three learning outcomes strands: knowledge (K), skills (S), and responsibility (R).

• PLO 01: Discuss and explain concepts and key components of robotics technologies.
• PLO 02: Compare and contrast various robot sensors and their perception principles that enable a robot to analyze their environment, reason, and take appropriate actions toward the given goal.
• PLO 03: Analyze and solve problems in spatial transformation, robot locomotion, kinematics, motion control, localization, and mapping, navigation, and path planning.
• PLO 04: Critically appraise current research literature and conduct rigorous and situationally appropriate experiments with state-of-the-art robotic algorithms on a robotic platform.
• PLO 05: Effectively communicate robotics concepts and design decisions using a range of media/visual mediums.
• PLO 06: Function effectively in or lead a team, that creates a collaborative and inclusive environment, establishes research goals, plans tasks, and meets desired objectives.

Completion Requirements

The minimum degree requirements for the Master of Science in Robotics are 36 credits, distributed as follows: | Number of courses | Credit hours | --- | --- | | Core | 5 | 16 | Electives | 2 | 8 | Internship | At least one internship of up to six weeks duration must be satisfactorily completed as a graduation requirement | 2 | Introduction to research methods | 1 | 2 | Research thesis | 1 | 8 | Total | 10 | 36

Core Courses

The Master of Science in Robotics is primarily a research-based degree. The purpose of coursework is to equip students with the right skillset, so that they can successfully accomplish their research project (thesis). Students are required to take core courses as mandatory courses. They can select a minimum of two electives.

• AI7101: Machine Learning with Python
• AI7102: Introduction to Deep Learning
• INT799: Master of Science Internship
• RES799: Introduction to Research Methods
• ROB701: Introduction to Robotics
• ROB703: Robot Localization and Navigation
• ROB7101: Robotic Manipulation and Control
• ROB799: Robotics Master's Research Thesis

Elective Courses

Students will select a minimum of two elective courses, with a total of eight (or more) credit hours based on interest, proposed research thesis, and career aspirations, in consultation with their supervisory panel.

• CBIO7101: Introduction to Single Cell Biology and Bioinformatics
• CS7201: Foundations of AI System Design
• CS7602: Computer and Network Security
• CV701: Human and Computer Vision
• CV702: Geometry for Computer Vision
• CV703: Visual Object Recognition and Detection
• CV707: Digital Twins
• CV7501: Selected Topics in Computer Vision
• CV7502: Deep Learning for Visual Computing
• DS701: Data Mining
• DS702: Big Data Processing
• ENT799: Entrepreneurship in Action
• HC701: Medical Imaging: Physics and Analysis
• ML701: Machine Learning
• ML707: Smart City Services and Applications
• ML708: Trustworthy Artificial Intelligence
• ML709: IoT Smart Systems, Services, and Applications
• ML710: Parallel and Distributed Machine Learning Systems
• ML7101: Probabilistic and Statistical Inference
• MTH7101: Mathematical Foundations for AI
• NLP701: Natural Language Processing
• NLP702: Advanced Natural Language Processing
• NLP703: Speech Processing
• ROB702: Robotic Vision and Intelligence

Admission Criteria

• Completed degree: MBZUAI accepts applicants who hold a completed bachelor's degree in a STEM field with a minimum CGPA of 3.0 (on a 4.0 scale) or equivalent.
• English language proficiency: All applicants whose first language is not English must demonstrate proficiency in English through one of the following: IELTS Academic, TOEFL iBT, PTE Academic, Cambridge C1 Advanced, Cambridge C2 Proficiency, or Duolingo English Test.
• Graduate Record Examination (GRE): Submission of GRE scores is optional for all applicants but will be considered a plus during the evaluation.
• Statement of purpose: In a 500- to 1000-word essay, explain why you would like to pursue a graduate degree at MBZUAI.
• Referee recommendation: Applicants will be required to nominate referees who can recommend their application.
• Screening exam: Within 10 days of submitting your application, you will receive an invitation to book and complete an online screening exam that assesses knowledge and skills relevant to your chosen field.

Admission Process and Key Dates

• Application portal opens: September 1, 2025
• Priority deadline: November 15, 2025
• Final deadline: December 15, 2025
• Decision notification date: March 15, 2026
• Offer response deadline: April 15, 2026

Study Plan

Students are expected to complete coursework in the first year of their degree and focus more on the research project and thesis writing in the second year.

• A typical study plan is as follows:
  • Semester 1: AI7101 Machine Learning with Python, AI7102 Introduction to Deep Learning, ROB701 Introduction to Robotics, and one elective.
  • Semester 2: ROB703 Robot Localization and Navigation, ROB7101 Robotic Manipulation and Control, and one elective.
  • Summer: INT799 Master of Science Internship.
  • Semester 3: RES799 Introduction to Research Methods and ROB799 Robotics Master's Research Thesis.
  • Semester 4: ROB799 Robotics Master's Research Thesis.