- Salary Package: Level A step 6 (PhD) to Level B from $91,188 - $125,405 p.a., plus 9.5% employer's superannuation and annual leave loading.
- Appointment Type:Full-time, 12 Month fixed term, with a possibility of further renewal subject to funding and performance.
- Working with leading researchers based in Macquarie University (North Ryde location)
Macquarie University is seeking a suitably qualified Postdoctoral Research Fellow to join a talented and pro active research team within the Optus Macquarie University Cyber Security Hub.
Reporting to the Executive Director of the Cyber Security Hub, you will:
• In collaboration with senior academic staff, carry out innovative, impactful research of strategic importance to the Cyber Security Hub leading to novel and important scientific outcomes.
• Publish research outcome in prestigious conferences and journals in the domain of privacy preserving technologies and related areas.
• Engage with Undergraduate and Higher Degree Research students to foster collaboration amongst the team members and jointly work on innovative privacy-related technologies.
• Design, evaluate and build privacy-preserving algorithms for machine learning.
You will have completed (or soon to complete) a PhD in a related discipline. You will assist and collaborate with a team of world-renowned researchers to work on different aspects of Privacy Enhancing Technologies (PETs) from the development of theoretical frameworks with cryptographic or information theoretic approaches, to the empirical and data-driven analysis of real-life applications and datasets.
The successful applicant will build trustworthy, reliable and secure systems within the Data Security and Privacy R&D Program led by the Information Security and Privacy Group of the Department of Computing at Macquarie University. They will work closely with collaborators from the Department of Computing, Macquarie Law School, and Center for Health Informatics.
The Optus Macquarie University Cyber Security Hub within the Faculty of Science and Engineering is an interdisciplinary network launched in August 2016 by Macquarie University with Optus as the founding partner.
About the Project
Privacy, Law and Ethics in Machine Learning as a Service is a Cybersecurity Hub Research Program Project under the Data Privacy and Security program. The project led by researchers from the Information Security and Privacy Group in Macquarie University and in collaboration with Macquarie Law School, and Center for Health Informatics, will (a) quantitatively assess information leakage when machine learning models are trained on sensitive health data by translating societal and legal expectations of privacy into their technical counterparts, and (b) to explore machine learning training techniques that are robust against data update scenarios stipulated by new privacy laws and ethical use of data (e.g., individuals requesting withdrawal of their data). The expected outcomes of the project are a knowledge sharing workshop with industry, new machine learning algorithmic techniques, and scholarly research publications on the findings.
To be considered for this position, please apply online and attach your resume and a separate cover letter that outlines how you meet to the selection criteria below:
- A PhD (or will shortly satisfy the requirements of a PhD) in a relevant discipline area, such as Computer Science, Mathematics or statistics, Cryptography and Information Security/Privacy.
- Demonstrated knowledge and skills in one or more of the following areas: Design and analysis of analytics algorithms, machine learning, differential privacy framework, and applied cryptography.
- Demonstrated experience in the collection and processing of large data sets, development of efficient algorithms on large datasets, and development of security or privacy-preserving algorithms, protocols for processing and sharing data or analytics and large-scale measurement studies of privacy and security risks.
- A record of science innovation and creativity plus the ability and willingness to incorporate novel ideas and approaches into scientific investigations.
- A record of publication in top peer reviewed journals and conferences (i.e. high impact factor, or selective acceptance rate).
- Ability to work within collaborative teams towards research objectives.
- Previous experience or research in privacy-preserving machine learning algorithms and data-driven quantification, risks assessment and attacks identification.
- Familiarity with software development processes and a few mainstream programming languages such as C, Python, Java and Web programming.
General Enquiries: Dali Kaafar, Executive Director on email@example.com
Applications Close: Sunday 6 September 2020 at 11:55pm
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