Research Fellow in AI for Industrial Control System Security

The Centre for Secure Information Technologies (CSIT) at Queen’s University Belfast, is currently seeking to appoint exceptional candidates to the posts of Research Fellow to perform research in the area of AI-enabled cybersecurity, called Cyber-AI.

The posts are associated with the newly-created Cyber-AI Technologies Hub, where CSIT will collaborate with cyber security companies located in Northern Ireland on research and development projects in AI-enabled cyber security. The Hub is of strategic importance for QUB in relation to meeting it's commitments to the Belfast Region City Deal. In addition, this project is making a contribution of £2.4M to the University.

The Cyber-AI Technologies Hub is a physical environment where companies and academia can collaborate on the advancement and demonstration of AI and cyber security. This is an exciting and unique opportunity for the right candidates to be involved in impact-focused research at the emerging Cyber-AI interface, and to help establish Northern Ireland as the go-to-region worldwide for innovation in Cyber-AI.

The successful post holder will be required to perform research in AI for industrial control system (ICS) security. The role involves gaining a deep understanding of how AI systems can be applied to secure ICS against malware and related advanced persistent threats (APTs) relevant to a partner company. A key requirement is to design explainable deep neural networks (DNNs), extending the latest state-of-the-art research into APT and anomaly detection using both proprietary and public datasets.

Among other duties, the post holder will:

• Undertake high- quality and novel research in deep- learning- based industrial control system (ICS) security. This will involve developing explainable anomaly detection and intrusion detection techniques that work with networking and industrial- process- based features and creating novel explainability techniques tailored to the ICS domain.
• Design, develop, and refine experiments to evaluate deep-learning-based ICS security system performance and explainability.
• Carry out analyses, critical evaluations, and interpretations using methodologies and other techniques appropriate to AI for ICS security.

About the person:

To be shortlisted for interview, candidates must clearly demonstrate how they meet the following essential criteria:

• Normally have or about to obtain a PhD in engineering or physical sciences area.
• Recent high quality research experience in machine learning/deep learning or cybersecurity, or both, as evidenced by a strong track record of publications in leading journals and conferences in relevant areas.
• roficient in Python. Experience using neural network libraries such as PyTorch, Keras, and/or TensorFlow.
• bility to design, train and test machine learning/AI systems using appropriate methodologies and datasets.

To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in the Candidate Information document on our website.

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