Postdoctoral Fellow in Distributed Systems Security and Privacy
PRIMARY DETAIL
*Salary Package: Level A step (6-8) from $95,706 to $102,570 per annum, plus 17% employer’s superannuation and annual leave loading
*Appointment Type: Full-time, fixed term for 3 years, with a possibility of further renewal subject to funding
*Macquarie University (North Ryde) location
THE ROLE
An exciting opportunity to join the Macquarie University Cyber Security Hub. We are looking for an enthusiastic researcher with expertise in distributed systems security and privacy, secure multi party computation, and/or Machine learning robustness including confidential computing and security.
The successful candidate will conduct high-quality research activities within the Cyber Security Hub at Macquarie University, led by Prof. Dali Kaafar, to research on topics including but not limited to:
- Machine learning robustness, with an emphasis on security and privacy, with the objective to quantify information leakage of AI platforms, as well as the associated security risks under adversarial settings. The candidate will (i) identify privacy and security risks in Machine Learning algorithms, focusing on sensitive real-world applications such as biometric recognition, and (ii) propose novel defense approaches for trustworthy, private, and secure machine learning.
- Distributed systems security, to contribute to projects and carry out research to develop robust detection and prevention techniques to make security decisions when faced with complex security problems in distributed systems.
- Secure multi party computation with the objective to study and develop provably private and secure distributed data analytics platforms with applications to real-life challenges including health informatics, intelligent transportation systems, critical infrastructure, critical Defence grade platforms, etc.
- Internet privacy and security, aiming to automatically detect and quantify privacy violations and security threats in the Web and Mobile Apps. The candidate will exploit active and passive measurements approaches and design methodologies to automate detection, risk assessment and control of security and privacy threats.
The candidate will work effectively as part of a multi-disciplinary research team, to undertake independent scientific investigations and carry out associated tasks under the guidance of senior Researchers and Academics.