- 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 dynamic team within the Data Security and Privacy R&D Program of 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.
• Develop an information theoretic framework to quantify information leakage through access to AI platforms. Design a defense algorithm against information leakage to make AI platform private. Build a RESTful API for customised privacy-preserving tasks.
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, composed of a multi-disciplinary group of researchers from across the university, led by the Information Security and Privacy Group and working closely with a larger collaborative team involving Defense Science and Technology DST Researchers and partners from Data61.
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
Data Privacy in AI Platforms (DPAIP)is a collaborative research project. The project led by researchers from the Information Security and Privacy Group in Macquarie University and in collaboration Defense Science and Technology (DST) and Data61, CSIRO, will (i) design, construct and validate an information leakage quantification framework which quantifies inference of ML model parameters and training data in AI platforms, (ii) design privacy-preserving techniques for use as defense apparatus embedded within AI platforms (so that training data subjects are guaranteed privacy through on-device privacy-preserving AI and data owners are guaranteed that proprietary datasets and models remain private), and (iii) implement proof-of-concept Application Programming Interfaces (APIs) for AI platforms enabling analytics services with built-in privacy and data security. The expected outcomes of the project are a knowledge sharing workshop with industry, new privacy-preserving 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 algorithms, machine learning, information theory, and differential privacy framework.
- 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 RESTful API development.
- Familiarity with software development processes and a few mainstream programming languages such as C, Python, Java and Web programming.
Enquiries: Dali Kaafar, Executive Director on email@example.com
Applications Close: Sunday 6 September 2020 at 11:55pm
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