Postdoctoral Research Fellow, Privacy Preserving Technologies
- Salary Package: From $90,188 - $96,655 p.a. (Academic Level A), plus 9.5% employer's superannuation and annual leave loading.
- Appointment Type: Full-time, 12 Month fixed term
- Working with leading researchers based in Macquarie University (North Ryde location)
Macquarie University are seeking a suitably qualified Postdoctoral Research Fellow to join a talented and dynamic team.
Reporting to the scientific 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 outcome of research in prestigious conferences and journals in the domain of privacy preserving technologies and related areas.
- Engage with Undergraduate students and High Degree students to foster collaboration amongst the team members and jointly work on innovative Privacy-related technologies.
- Design, evaluate and build algorithms for the DataRing platform for private analytics extraction.
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 theoretical 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 Information Security and Privacy Group of the Department of Computing at Macquarie University. They will work closely with collaborators from the NSW Cyber Security Network and industrial partners in the Data Ring Project.
The Optus Macquarie University Cyber Security Hub is an interdisciplinary network launched in August 2016 by Macquarie University with Optus as the founding partner.
DataRing is a project funded by the NSW Cyber Security Network, an initiative from New South Wales Government, Data Republic and the Optus Macquarie University Cyber Security Hub to conduct world-class research in privacy-preserving analytics. The project led by researchers from the Information Security and Privacy Group in Macquarie University and in collaboration with UTS, will design, construct and validate algorithms enabling private extraction of data analytics while guaranteeing a consensus of privacy versus utility. We aim to build a platform to demonstrate the data ring and test it on an Optus use case. The platform will enable data custodians' assessment of threats and distributed analytics extraction.
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 distributed analytics algorithms, differential Privacy framework, Applied Cryptography, Game Theory, machine learning and Information theory, Modelling, Probabilistic and statistical 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 either theoretical frameworks for Privacy preserving algorithms or data-driven quantification and 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, Scientific Director on email@example.com
Applications Close: Thursday, 3 January 2019 at 11:55pm (AEST )
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