We are seeking an exceptional PhD candidate to join our cutting-edge research projects aimed at developing innovative solutions to enhance cyber security with deep learning-based continuous monitoring and response systems for real-time security incident detection and response in zero trust environments. The focus of this PhD research will be on developing and evaluating deep learning-based algorithms and techniques that can continuously monitor the behaviour of users, devices, and networks in real-time to detect potential security incidents and respond to them before they cause any harm.
The candidate will explore different deep learning models like Recurrent Neural Network (RNN), Generative Adversarial Network (GAN), and deep Reinforcement Learning (RL) to improve the identification performance, and work on developing novel approaches to address key security challenges such as developing and evaluating deep learning-based models for anomaly detection in user and device behaviour, network traffic, and application usage patterns. Additionally, the candidate will design and implement real-time response systems that can automatically take actions such as blocking or isolating potentially compromised devices or users and investigate the use of advanced deep learning techniques to improve the accuracy and efficiency of real-time security incident detection and response.
The candidate will also work on developing reinforcement learning-based adaptive access control mechanisms to dynamically adjust access privileges based on user and device behaviour.
As part of our research team, the candidate will have access to state-of-the-art research facilities and work with a highly collaborative and interdisciplinary team of researchers from different fields. The candidate will also have opportunities to present their research findings at top-tier conferences and publish in high-impact academic journals.
Entry requirements:
The ideal candidate should have or expect to achieve at least a 2:1 Honours degree (or equivalent) in Computer Science, Cyber Security, or a related subject. A relevant master’s degree and/or experience in one or more of the following will be an advantage: Natural Language Processing, Computer Vision, or Deep Learning. The applicant should also have strong programming skills in machine learning and more particularly deep learning (PyTorch, TensorFlow and, Keras,) is an asset, and be familiar with C/C++, various scripting languages and with the Linux environment.
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