MSc Robotics and Artificial Intelligence

1 Years On Campus Masters Program

Queens University Belfast

Program Overview

This MSc offers a cutting-edge programme combining robotics, artificial intelligence, machine learning, computer vision and control of dynamical systems—all in one year of full-time study. It suits students who have a strong background in engineering, computer science, mathematics or a related field and aspire to design, build and deploy intelligent robotic systems or engage in research at the intersection of robotics and AI.

Curriculum Structure
Year 1 (single-year intensive): In the Autumn term students focus on core foundational modules such as Foundations of AI and Machine Learning, which develop mathematical and algorithmic skills for intelligent systems. Then in the Spring term they advance into hands-on modules like Mechatronics for Robotics (covering embedded software/hardware with microcontrollers, sensors and actuators) and Robotics (focusing on kinematics, dynamics, robot control and architectures with ML/AI applications) and Computer Vision (covering classical and deep learning approaches to image/video tasks). In the summer term they complete a Themed Research Project (an independent MSc dissertation) working on applied robotics/AI problems—say mobile robots, UAVs, manipulators or human-robot interaction in collaboration with the university’s labs.

Focus areas:
Robotics & autonomous systems; embedded hardware-software mechatronics; machine learning & AI for robotics; computer vision; control and estimation of dynamical systems.
Learning outcomes:
Graduates will be able to design and analyse robotic and intelligent systems, implement machine-learning & AI techniques in robotic contexts (e.g., vision, manipulation, mobile autonomy), control and estimate complex dynamical systems, and carry out independent research or development projects.
Professional alignment (accreditation):
The course is housed in Queen’s University Belfast’s School of Electronics, Electrical Engineering and Computer Science, and leverages world-class facilities including the £10 m renovated robotics/autonomous-systems labs.
Reputation (employability rankings):
Queen’s University Belfast is a well-established Russell Group institution with strong research output in AI/robotics; its investment in advanced manufacturing innovation facilities and partnerships enhances the employability of graduates from robotics/AI programmes.

Experiential Learning (Research, Projects, Internships etc.)

Students in the MSc Robotics and Artificial Intelligence at Queen’s University Belfast engage in a deeply hands-on programme where theory meets real-world engineering and AI practice. They work in recently refurbished labs and innovation centres, using modern hardware and software tools in robotics, mechatronics, computer vision, AI and systems control. Through individual research projects, collaborative challenges and industry-aligned environments they build both technical proficiency and professional readiness. They also draw on Queen’s strong links to manufacturing innovation and robotics research so that their learning connects directly to current engineering and AI practice.

Key experiential components include:

State-of-the-art facilities: Students access laboratories for Robotics & Autonomous Systems, Micro-engineering, Electronics, Instrumentation and Virtual Reality, in a facility recently boosted with an investment of around £10 million. These spaces support experimental work in robotics hardware, mechatronics, circuits and embedded systems.
Major innovation centre collaboration: The programme is tied to the university-led Advanced Manufacturing Innovation Centre (AMIC), an open-access manufacturing & engineering innovation centre. This enables students to work in industry-facing settings, engage with real manufacturing/robotics problems and access professional equipment and project opportunities.
Specialist software & hardware tools: The curriculum covers embedded microcontrollers, sensors and actuators (via the “Mechatronics for Robotics” module), computer vision and machine-learning algorithms, robot kinematics/dynamics and control systems. These are practiced in lab work, simulation and project builds using relevant programming and AI environments.
Team-based and individual research project: In the summer term students undertake an independent themed research project (e.g., motion planning, human-robot interaction, UAVs, robotic manipulators) often drawing on industry-sponsored proposals and the university’s lab resources.
Virtual learning environments and group work: Modules are supported by an online learning platform (Canvas), with substantial lab and contact time (around one module per day for 6–7 hours during semesters) and opportunities for group work which simulate professional engineering teamwork.
Transferable skills and professional readiness: The programme explicitly emphasises development of skills beyond technical ones — including communication, time-management, research thinking, CV/interview skills and working in interdisciplinary teams — preparing graduates for engineering or research careers in robotics and AI.

Progression & Future Opportunities

Graduates from the Queen’s University Belfast MSc in Robotics and Artificial Intelligence are equipped to step into roles such as Robotics Systems Engineer, Artificial Intelligence Developer, Autonomous Systems Engineer and R&D Engineer in robotics and automation industries. They emerge ready for both technical development roles and further research opportunities:

University services: The university supports students through its Careers, Employability and Skills team, offering CV workshops, interview preparation and links with industry partners. The School of Electronics, Electrical Engineering & Computer Science also runs dedicated revision and mathematics support services.
Employment & salary: While specific salary figures for this exact programme aren’t published, the course page emphasises that it “prepares students for a successful career path in industries” through hands-on skills in robotics, AI, mechatronics and vision systems.
University–industry partnerships: The programme benefits from state-of-the-art facilities including the newly established Advanced Manufacturing Innovation Centre (AMIC), led by Queen’s, which is an industry-led, open-access manufacturing and engineering innovation centre. Also, the university’s AI Collaboration Centre supports funded postgraduate AI-related places and works closely with industry to drive AI innovation across sectors.
Long-term accreditation value: The degree’s strong foundations in control systems, embedded software/hardware, machine learning and vision systems provide a long-term value in rapidly evolving fields. The university’s engineering school emphasises professional readiness and industry relevance.
Graduation outcomes: Beyond taught modules like Foundations of AI, Machine Learning, Mechatronics for Robotics, Robotics, Computer Vision and Control, students carry out a themed research project which often involves mobile robots, UAVs or manipulators and may be industry-sponsored.

Further Academic Progression:
After completing this MSc, students can progress to a PhD in Robotics, Autonomous Systems or Artificial Intelligence, leveraging Queen’s strong research groups in mechatronics, vision and control systems. Alternatively, they could pursue specialised professional certifications or postgraduate diplomas in areas like control systems engineering, AI for healthcare, or autonomous vehicle systems—preparing for leadership or specialist roles in industry.