- Are you a highly motivated recent (or near) PhD graduate with expertise designing algorithms?
- Prestigious Postdoctoral Fellowship on offer - kick-start your research career
- Join CSIRO's Data61 - Australia's largest data innovation group
Privacy-preserving technologies are now critical as evermore volumes of data are being collected and shared between entities. Releasing and analysing data in a privacy-preserving manner means that any information specific to an individual remains hidden while characteristics common across individuals are learned. A series of results have shown that the pervasive techniques of de-identification (removing obvious identifiers of individuals from data) to sanitise datasets are prone to a host of attacks including inference and re-identification through use of background knowledge. A safer alternative is to use provably privacy-preserving algorithms to release and analyse data.
We are seeking a Postdoctoral fellow to work on different aspects of Privacy Enhancing Technologies (PETs) as applied to problems arising in privacy preservation of real-world datasets. The Postdoctoral fellow will be involved in one or more projects in three focus areas:
- Designing algorithms and protocols that allow private release and/or analysis of data for different application scenarios. These include online access to data through a secure interface, one-off release of synthetic data, real-time release of statistics from continuous streams of data, and data aggregation at the edge in an Internet-of-Things (IoT) setting.
- Application and implementation of private algorithms for release and analysis of real-world industry and government datasets in ongoing and future data privacy projects. This will involve identification and development of suitable algorithms (in terms of computational efficiency and utility) targeted to a particular dataset and statistical insights.
- Examining and introducing variants of provable privacy definitions that improve trade-off between privacy and utility.
The outcome of this research will have both research and practical applications. The successful candidate will closely interact with both researchers and engineers within the Information Security and Privacy Group.
Location: Sydney, NSW
Salary: AU $80K - AU $91K plus up to 15.4% superannuation
Tenure: Specified Term of 3 years
To be successful you will need:
- A doctorate (or will shortly satisfy the requirements of a PhD) in a relevant discipline area, such as Theoretical Computer Science, Algorithms, Mathematics with a computing major, Cryptography and Information Security/Privacy.. Please note: To be eligible for this role you must have no more than 3 years of relevant postdoctoral experience.
- Demonstrated knowledge and skills in one or more of the following areas: Design and analysis of algorithms, Differential Privacy framework, Applied Cryptography, Probabilistic and statistical framework, machine learning and Information theory.
- 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 or protocols for processing and sharing data.
- The ability to work effectively as part of a research team, plus the motivation and discipline to carry out autonomous research.
- 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).
Before applying, we encourage you to read the full position description for this role. This document can be viewed at:
Position details document
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How to Apply: To apply, please provide a CV as well as a cover letter addressing the selection criteria in brief, and upload these as one document. If your application proceeds to the next stage you may be asked to provide additional information.
Applications Close: Applications will remain open until filled.