⛔ This position is no longer available.
University: University College London
Country: United Kingdom
Deadline: 2026-04-10
Fields: Computer Science, Artificial Intelligence, Cybersecurity, Machine Learning, Information Systems
Topic: United Kingdom – Fully Funded PhD in Explainable AI for Systems Security at University College London
Fields: Computer Science, Artificial Intelligence, Cybersecurity, Machine Learning, Information Systems
Position: PhD
Country: europe
Deadline: 2026-04-10
University: University College London
Real Country: United Kingdom
Main Category: computer & data sciences
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Are you passionate about advancing the frontiers of artificial intelligence and machine learning to solve real-world security challenges, while ensuring that these technologies remain transparent, trustworthy, and supportive of human experts? If you aspire to make a tangible impact in the rapidly evolving domain of systems security, this fully funded PhD opportunity at University College London (UCL) Computer Science could be the perfect next step in your academic journey.
About the University or Research Institute
University College London (UCL) is one of the world’s leading multidisciplinary universities, renowned for its cutting-edge research, academic excellence, and vibrant international community. Located in the heart of London, UCL offers a dynamic and intellectually stimulating environment, fostering innovation across a diverse range of disciplines. The Department of Computer Science at UCL consistently ranks among the top in the United Kingdom and globally, recognized for pioneering contributions to artificial intelligence, cybersecurity, and human-centered computing. UCL’s central London location provides unparalleled access to industry partners, government agencies, and a thriving technology ecosystem, making it an ideal setting for impactful research and professional growth.
Research Topic and Significance
The focus of this PhD position is on developing explainable, knowledge-driven AI and machine learning (ML) techniques specifically tailored for systems security. With the increasing integration of AI and ML into security applications, there is a pressing need to ensure these technologies are not only effective but also interpretable and trustworthy. Recent advances such as large language models (LLMs) and agentic AI systems have opened new possibilities for automating threat detection, investigation, and response. However, these innovations also introduce unique security and privacy challenges, including novel attack vectors and unpredictable behaviors in complex environments.
This research aims to bridge the gap between state-of-the-art AI/ML and their practical deployment in adversarial security settings. By developing robust, explainable, and user-centered AI solutions, the project seeks to empower both automated defenses and human analysts, ultimately enhancing the security and resilience of critical systems. The significance of this work extends to addressing cognitive overload for analysts, improving the transparency of AI-driven decisions, and ensuring that security tools are genuinely beneficial in real-world scenarios.
Project Details
The PhD project will be supervised by Dr. Fabio Pierazzi, an established expert in AI for systems security. The research direction offers flexibility and can be tailored to the candidate’s strengths and interests, encompassing areas such as:
– Designing advanced AI-driven systems for complex security tasks beyond simple threat detection, including multi-step intrusion analysis and cross-domain threat hunting.
– Evaluating the trade-offs and vulnerabilities of Small Language Models (SLMs) in security applications, considering performance, cost, and deployment challenges.
– Investigating the security implications of agentic AI systems, particularly their potential to introduce new attack surfaces in automated intrusion response and threat investigation.
– Conducting user studies and empirical evaluations with security analysts to identify pain points and ensure that developed tools meet practitioners’ needs.
– Developing interpretable models and tools that foster trust and collaboration between AI systems and human experts.
– Establishing robust evaluation frameworks and datasets that reflect realistic, evolving security environments.
The overarching ambition is to deliver research outcomes that have genuine practical impact, empowering both automated defenses and human analysts in the ongoing battle against sophisticated cyber threats.
Candidate Profile
This opportunity is ideal for candidates who possess:
– A BSc or MSc in Computer Science or a closely related discipline.
– A strong foundation in artificial intelligence, machine learning, and/or systems security.
– Interest in trustworthy and explainable AI for security applications.
– Programming experience, ideally in Python.
– Motivation, curiosity, and a commitment to high-quality research.
– The ability to work independently and collaboratively, with an openness to interdisciplinary approaches.
– Willingness to bridge gaps in expertise between AI and cybersecurity, as deep experience in both is not strictly required.
Applicants should be eager to contribute their own ideas and shape the research direction in alignment with the supervisor’s vision and the evolving needs of the field.
Application Process
– Application Deadline: 10 April 2026
– Eligibility: Open to Home/UK applicants only. For details on home fee status and eligibility, refer to the UK government guidance and UCL fee status guidance.
– Programme: UCL Computer Science 4-Year Programme (MPhil/PhD)
– Application instructions and further details are available at the official reference link below.
Please refer to the official advertisement for application details.
For more information, see: https://fabio.pierazzi.com/opportunity/phd-ucl-cs-2026
Conclusion
This fully funded PhD position at UCL Computer Science offers a unique opportunity to contribute to the advancement of explainable and knowledge-driven AI for systems security. If you are motivated to address real-world security challenges and passionate about making AI more transparent, trustworthy, and supportive of human experts, you are encouraged to apply. Explore the official advertisement for further details, and consider following similar opportunities to advance your academic and professional career in this dynamic field.
Questions & Answers
Question: What makes UCL Computer Science a strong choice for research in AI and systems security?
UCL Computer Science is globally recognized for its pioneering research, strong industry connections, and vibrant academic community. Its central London location provides access to leading experts, events, and opportunities for impactful collaboration.
Question: Who is eligible to apply for this PhD position?
Eligibility is restricted to Home/UK applicants, as defined by UK government and UCL fee status guidance.
Question: What are the main research themes within this PhD opportunity?
The research themes include explainable AI, robust machine learning for security, user-centered security tools, evaluation of language models in adversarial settings, and empirical studies with security analysts.
Question: Is prior experience in both AI and cybersecurity required?
A strong foundation in either AI/ML or cybersecurity is important, but deep experience in both is not mandatory. Curiosity and a willingness to learn across disciplines are highly valued.
Question: What skills should applicants have?
Applicants should have a background in computer science or a related field, programming experience (ideally Python), and an interest in trustworthy AI for security.
Question: How can candidates tailor their research within this PhD?
The project scope is flexible and can be aligned with the candidate’s strengths, interests, and proposed ideas, as long as they are connected to the supervisor’s research vision.
Question: What is the expected start date for this PhD programme?
The expected start date is October 2026.
Question: Where can I find more information about the application process?
Detailed information and official guidelines can be found at: https://fabio.pierazzi.com/opportunity/phd-ucl-cs-2026
Want to calculate your PhD admission chances? Try it here:
https://phdfinder.com/2026/03/12/phd-admission-chance-calculator/
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