Course Overview

The MSc in Intelligent Robotics provides students with the knowledge and skills in AI, computer vision, simulation, robotics and automation required for the rapidly evolving field of Intelligent Robotics.   

 

At the end of this program, students will be able to: 

  • Develop computer vision systems for automated classification and inspection tasks 
  • Develop digital twins for the design and implementation of robotics systems 
  • Design and implement sensing and perception systems for autonomous and robotic systems 
  • Design and implement control, navigation and locomotion for autonomous vehicles and robotic systems 
  • Design and implement advanced manufacturing techniques, including additive manufacturing, milling/drilling, cutting/welding, curing etc. 

Applications and Selections

Applications are made online via the University of Galway Postgraduate Applications System.  

Applicants must submit a filled out Electrical and Electronic Engineering Project Form to the 'Other Documents' section of the application form.

Who Teaches this Course

Indicative list of those teaching the course (with their School):  

 

 

Edward Jones (Engineering) 

Peter Corcoran (Engineering) 

Adnan Elahi (Engineering) 

Liam Kilmartin (Engineering) 

Brian Deegan (Engineering) 

Kathryn Cormican (Engineering) 

Mary Dempsey (Engineering) 

Martina Kelly (Engineering) 

Noel Harrison (Engineering) 

Requirements and Assessment

Key Facts

Entry Requirements

Application to the programme is open to individuals who have Second Class Honours, Grade 1 (H2.1) or equivalent in a Level 8 BE, BSc or equivalent degree in Electrical/Electronic/Computer/Mechatronic Engineering, or Computer Science, from a recognised university or third-level college. Applications from those holding a primary degree in a cognate discipline will be assessed on a case-by-case basis. Factors considered in determining admission will include the specific content of the undergraduate degree, the applicant’s performance, postgraduate experience, and the availability of places. 

Additional Requirements

Recognition of Prior Learning (RPL)

Duration

1 year, full time

Next start date

September 2024

A Level Grades ()

Average intake

10

QQI/FET FETAC Entry Routes

Closing Date

1st September 2024

NFQ level

Mode of study

ECTS weighting

90

Award

CAO

Course code

MIR1

Course Outline

The MSc in Intelligent Robotics is a 90 ECTS (Credits) programme, which includes a taught component of 60 ECTS (delivered in Autumn and Spring Semesters), with a Research Thesis of 30 ECTS, on a state-of-the-art topic in intelligent robotics undertaken over the entire year of the programme.  

All students complete the Research Thesis component. Students also choose from a number of advanced discipline-specific technology modules covering topics such as: signal and image processing, computer vision, artificial intelligence, autonomous navigation, digital twins, embedded systems and Internet of Things design, electronic circuit design, sensor systems. Students must select modules with a combined credit weighting of 45-50 ECTS.  

A range of Engineering Transferable Skills modules enable students to develop skills in business, innovation, regulatory and research methods, while also providing options for training in advanced mathematical techniques and information technology. These modules will prepare students for lifelong learning and development in a professional engineering career, either in industry or in a research environment. Students must choose 10-15 ECTS of modules from the Transferable Skills category.  

Indicative list of discipline-specific modules (note: The specific range of modules from which students may choose may vary from year to year, depending on module availability, and student demand): 

 

  • Robotic Control, Navigation and Locomotion 
  • Embedded Image Processing 
  • Embedded Computer Vision 
  • Sensing and Perception for Automation and Robotics 
  • Advanced Manufacturing 
  • Digital Twins for Robotics 
  • Mobile Device Technologies 
  • Mobile Networks: Architecture and Services 
  • Data Analytics 
  • Internet of Things Systems Design 
  • Digital Signal Processing 
  • Machine Learning 
  • Computer Security & Forensic Computing 

 

Indicative List of Transferable Skills modules: 

  • Financial management 
  • Technology, Innovation and Entrepreneurship 
  • Research Methods for Engineers 
  • Lean Systems 
  • Project Management 
  • Safety Engineering 
  • Introduction to Sustainability  

Why Choose This Course?

Career Opportunities

Graduates of this program will access diverse career pathways in emerging fields across a wide range of industries. Opportunities include roles in autonomous vehicle technology, where skills in robotics, computer vision, and control systems are in high demand. Industries such as advanced manufacturing, IoT, artificial intelligence, and data analytics will also seek their expertise, providing pathways to roles in innovation, research, and development. The program  

positions graduates for impactful careers, spanning sectors at the forefront of technological advancements, ensuring they contribute to shaping the future of science, engineering, and sustainable innovation. 

Who’s Suited to This Course

Learning Outcomes

Transferable Skills Employers Value

A range of Engineering “Transferable Skills” modules enable students to develop skills in business, innovation, regulatory and research methods, while also providing options for training in advanced mathematical techniques and information technology. These modules will prepare students for lifelong learning and development in a professional engineering career, either in industry or in a research environment. Students must choose 10-15 ECTS of modules from the Transferable Skills category. 

Work Placement

Study Abroad

Related Student Organisations

Course Fees

Fees: EU

€8,640 ( including levy) p.a. 2024/25

Fees: Tuition

€8,500 p.a. 2024/25

Fees: Student levy

€140 p.a. 2024/25

Fees: Non EU

€27,000 p.a. (€27,140 p.a. including levy) 2024/25

Find out More

Programme Director: Prof Martin Glavin

Email: martin.glavin@universityofgalway.ie