Computer Science - Adaptive Cybersecurity

Course Overview

Cybersecurity is one of the most exciting and fastest growing areas of the ICT industry. It is a domain of enormous economic and societal importance, as it is aimed to protect citizens, businesses, and organisations against increasingly complex, damaging, and sophisticated attacks.



This increasing complexity and level of sophistication requires new means of attack detection, protection, and mitigation, which are addressed by this innovative new programme, the MSc in Computer Science (Adaptive Cybersecurity) offered by the University of Galway.



Adaptive cybersecurity incorporates state-of-the-art advanced dynamic cybersecurity techniques, algorithms, and frameworks to efficiently protect and mitigate systems and organisations against new emerging threats.



This 12-month full-time programme provides cutting edge technical training and research opportunities in the emerging area of AI-driven and data analytics-driven cybersecurity. It is a unique offering that is only matched by a small number of European and US-based Universities and builds on the vast research experience and technical skills of renowned, interdisciplinary experts based in the School of Computer Science, University of Galway.



This programme is aimed at graduates with a primary qualification and / or extensive industry experience in Computer Science or related subject area. It is not a conversion programme but expects students to already be at a very high standard regarding their Computer Science education.



Transferable Skills Employers Value

• Develop skills needed for sustained critical reflection.

• Enhance skills in the area of problem solving through engagement with difficult organisational and technical (cyber-) security questions.

• Enhance students’ skills in research, communication, and innovative thinking.

• Identify the general principles that connect problems and thereby evaluate the strengths and weaknesses of cybersecurity measures in an organisation. [Critical Reasoning]

• Conduct structured, educated and result-driven research on a known threat, as well as the ability to perceive potential future threats and their mitigations. [Analytical Skills]

• Communicate difficult ideas in a clear and persuasive manner, while listening to problems/ideas/proposals, and understanding and providing different points of view. [Communication Skills]

• Look at problems from diverse points of view. [Design and Planning Skills]

• Identify a security problem and formulated questions relevant to clarifying the threat(s)/issue(s). [Research and Investigation Skills].



Lectures are complemented by weekly labs and tutorials.

Students will collect 90 ECTS during 12 months of full-time studies. The programme covers over two semesters many complementary areas of Cybersecurity, Artificial Intelligence, and Data Analytics, including Intrusion Detection and Malware Analysis, Secure DevOps, Ethics & Data Privacy, Deep Learning, Case Studies in Cybersecurity Analytics, Autonomous Agents and Multi-Agent Systems. Further on, students reinforce their newly gained skills in a project that is completed during the summer.



During semester 1 students will focus on foundation topics comprising of 5 core modules and one elective module (30 ECTS in total) as follows:



Core Modules:

CT5165: Principles of Machine Learning

CT5189: Introduction to Cybersecurity

CT5191: Network Security & Cryptography

CT5190: Societal Impact of AI and Cybersecurity

CT5132: Prog. and Tools for AI



Elective Modules

CT5141: Optimisation

CT5120: Natural Language Processing 1

CT561: System Modelling and Simulation

CT5105: Tools & Techniques for Large Scale DA



During semester 2 advanced topical areas will be covered, again comprising of 5 core modules and one elective module (30 ECTS in total) as follows:



Core Modules:

CT5133: Deep Learning

CT5100: Data Visualisation

CT5192: Secure DevOps

CT5193: Case Studies in Cybersecurity Analytics

CT5194: Malware and Intrusion Detection



Elective Modules

CT5134: Agents, Multi-Agent Systems and Reinforcement Learning

CT5121: Advanced Topics in NLP

CT5113: Web & Network Science

CT5187: Knowledge Representation



Please see Course Web Page above for module details.

Prior qualification

• This MSc is targeted at high-performing graduates of Level 8 computer science programmes, or Level 8 science/engineering programmes that offer sufficient training in computing.

• The minimum academic requirement for entry to the programme is a First Class Honours (or equivalent) from a recognised university or third-level college. However, a good Second Class Honours (or equivalent) can be deemed sufficient on the recommendation of the Programme Director.

• English language proficiency

Overall, entry to the MSc Artificial Intelligence requires a minimum IELTS score of 6.5 overall, 6.5 in Writing and no less than 6.0 in any other band. TOEFL: Overall 88, Listening 12–19, Speaking 18–19, Writing 24–26, Reading 13–18. PTE: Overall 61, Writing 61, all other bands no less than 50.

• Applicants are required to submit a personal statement outlining:

o A summary of your primary degree and its relevance for a successful completion of this programme. We strongly encourage an evidence based approach to highlighting your academic accomplishments.

o A summary of your previous capstone projects (e.g., undergraduate final year projects) including an outline of your exact contribution there. We strongly encourage an evidence based approach to outlining your existing technical skills and experience



• Please upload a current C.V.

Closing Date: No set closing date. Offers made on a continuous basis.



Applications must be completed online at: https://nuigalway.elluciancrmrecruit.com/Apply/Account/Login.



An application requires a registration fee of €35. You will be asked to upload proof of identification, academic transcripts, a personal statement, an academic reference and documentation to fulfil the English requirement (where English is not your first language).

1 year full-time.

Next start date: September 2025

Career Opportunities

The high global demand in cybersecurity experts is being reflected in a range of career options for example as network security architect, cybersecurity operations analyst or information security analyst.



While our graduates can compete for such jobs, the programme, in particular, will cater for the demand stemming from emerging R&D career paths in cybersecurity that have a strong focus on machine learning and data analytics. These include positions such as an AI security controls architect, cybersecurity data analytics engineer, or cyber intelligence analyst.