Qualification : MASTER OF SCIENCE DEGREE
Award Type and NFQ level : TAUGHT MASTERS (9)
CAO/MU Apply code : MHJ21
CAO Points :
Closing Date : 30 August 2025
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 Maynooths 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:
1. Students from a computing background are introduced to the engineering principles of control theory, digital signal processing and robotics.
2. 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.
Candidates should have a minimum 2.1 grade honours (level 8) degree in a cognate discipline such as engineering, computer science, physics or maths or their international equivalent.
Candidates with a minimum 2.2 grade honours (level 8) degree in any discipline who can demonstrate at least five years of experience in software, embedded systems, or firmware development will also be considered. In exceptional circumstances, consideration will be given to candidates who do not hold a primary degree but have at least 10 years of relevant work experience in a software development, embedded systems or firmware role.
Candidates will provide evidence of proficiency in a high-level computer language of their choice.
Applicants must have a recognised primary degree which is considered equivalent to Irish university primary degree level.
Minimum English language requirements: please visit Maynooth University International Office website for information about English language tests accepted and required scores. The requirements specified are applicable for both EU and non-EU applicants.
National University of Ireland Maynooths TOEFL code is 8850
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Department of Electronic Engineering
Department of Faculty of Science & Engineering
Department of Hamilton Institute
Department of Radiospace
Department of Registry
Department of Registrar's Office
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Academic
Department of Electronic Engineering
Department of Hamilton Institute
Department of Computer Science
Department of Human Health Institute
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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.
Applications for postgraduate courses will open mid-October. Further information on how to apply for the course will be provided then. If you have any queries please contact [email protected].