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MSC ROBOTICS AND EMBEDDED AI
This 3-year part-time MSc provides graduates in computing, engineering, and cognate disciplines with specialised training in the design and control of intelligent machines.
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- Qualification
- Master Of Science Degree
- CAO/MU Apply code
- MHJ21
- Award Type and NFQ level
- TAUGHT MASTERS (9)
- Study Mode
- Part time
- Closing Date
- 27 August 2027
Overview
The Robotics and Embedded AI MSc will provide graduates in computing, engineering, and cognate disciplines with specialised training in the design and control of intelligent machines. Robotics is a multi-disciplinary field of study requiring skills in computing, electronics, and mechanical engineering.
Teamwork, innovation and the validation of science through practice are central to this success in this field. The program has a large team project each semester where students explore the application of the theories of robotics with a focus on design thinking and innovation in first semester and system realisation and evaluation in the second semester. In the third semester, they undertake a large independent research project in partnership with industry or the robotics research group.
The programme builds on the strong foundations of Maynooth’s undergraduate degrees in Computer Science (CS) and Robotics and Intelligent Devices (RID) undergraduate programmes. Many of the specialised 4th-year modules from these programmes are part of the MSc degree. They are supplemented by specialised training in deep learning, augmented reality, human-robot interaction, robot ethics and cognitive robotics.
Given the diverse backgrounds of the student intake, the programme provides two main pathways:
- Students from a computing background are introduced to the engineering principles of control theory, digital signal processing and robotics.
- For students coming from an engineering or robotics background, some courses focus on AI, deep learning and computation.
The dissertation research project will be available in two forms: a traditional project based in an academic research lab or a project undertaken as part of an internship with robotics firms who are supporting the programme, such as Eiratech Robotics, Combilift, Intel, Ubotica, Fanuc Robotics, Akara Robotics, Otherlab, etc.
Upon graduation, the students will be thoroughly grounded in robotics theory and cutting-edge research. They will also have developed transferable skills in design thinking, innovation, and teamwork. And finally, they will have demonstrated their newfound skills by completing a research project at the cutting edge of robotics and embedded AI.
Course structure
Duration: 3 years part-time
Programme learning outcomes:
1. Demonstrate knowledge of current technologies in sensing, actuation and cognition for robot and embedded AI systems.
2. Demonstrate skills in the construction and evaluation of robotic and embedded AI systems.
3. Demonstrate awareness of the societal context of developing robotic and embedded AI systems in terms of safety, ethics and privacy.
4. Demonstrate transferable skills of teamwork and communication while executing complex technological projects.
5. Demonstrate knowledge of the innovation management process and its linkage to the commercial and environmental sustainability of robotics and embedded AI systems.
Disclaimer
The modules below are indicative of the content associated with this course of study.
The modules are subject to change as the curriculum is revised and reviewed annually.
Important: The information on this page is for prospective students, MU current students and staff should use Programme Directory.
Year 1
Year 2
Year 3
Careers after your Masters
Completing a master's program in Robotics and Embedded AI opens the door to compelling career opportunities. Graduates can pursue roles as robotics engineers, specialising in designing and maintaining robotic systems, or as AI Engineers, focusing on developing AI algorithms for robotic applications. They may also become embedded systems developers, working on the software and hardware that control robotic devices and IoT systems, or automation engineers, automating processes in various industries. Research positions, either in academia or industry, offer the chance to contribute to advancing robotics and AI technologies. Alternatively, graduates can enter product development, software development, data science or autonomous vehicle engineering. Entrepreneurial individuals may even start ventures in this rapidly evolving field, catering to various industries and applications. The possibilities are diverse and dynamic, driven by one's interests and expertise.
Entry Requirements
Applicants must hold a minimum of a Bachelor Honours degree (NFQ Level 8) (or equivalent) with a minimum of a Second-Class Honours, Grade 1 (2:1) in a cognate discipline such as engineering, computer science, physics or maths. Programming experience is an essential requirement, and applicants must provide evidence of proficiency in programming, particularly in Python and/or C++.
If you do not meet the standard entry requirements then you may be eligible to apply under the University's Recognition of Prior Learning (RPL) policy. Please click here for further information.
Applicants for whom English is not their first language are required to demonstrate their proficiency in English in order to benefit fully from their course of study. For information about English language tests accepted and required scores, please see here.
How to apply
Applications must be made via the MU Apply portal. Please click here to start your application.
When making your application, please ensure you prepare any documents listed below. You may be required to submit documents in two stages. You will be required to upload and submit the following documents with your application:
- Full academic transcripts for all semesters/ years completed to date
- Graduation Certificate if you have graduated
- A copy of your passport
- Up to date CV
If English is not your first language, you may be required to upload evidence of English language proficiency. For information please click here.