• Salary Package: Level A step 6 (PhD) from $91,188 - $98,588 p.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)

The Role

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, machine learning and related areas. 
• Engage with undergraduate and higher degree students to foster collaboration amongst the team members and jointly work on innovative privacy-related technologies and privacy-preserving machine learning. 
• Design methods to assess privacy implications of machine learning models and develop alternative algorithms to mitigate these privacy issues for the “Data Privacy in Artificial Intelligence Platforms” (DPAIP) project.

About You

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 in machine learning. This includes development of theoretical adversarial and information leakage models, mathematical as well as empirical (data-driven) analysis of real-life applications and datasets used in machine learning as a service, and design and implementation of proof-of-concept mitigation techniques.

The successful applicant will analyse privacy issues in machine learning models and build privacy-preserving alternatives within the Information Security and Privacy Group of the Department of Computing at Macquarie University. They will work closely with collaborators from the Data61 (CSIRO), the Defence Science and Technology (DST) Group and industrial partner Singtel Optus.

About Us

The Optus Macquarie University Cyber Security Hub is an interdisciplinary network launched in August 2016 by Macquarie University with Optus as the founding partner.

DPAIP is a project funded by the DST Group, and involves the Optus Macquarie University Cyber Security Hub, Data61 (CSIRO), Swinburne University, and Singtel Optus. The project, led by researchers from the Information Security and Privacy Group in Macquarie University, aims to build a quantification framework of information leakage through machine learning models, designing privacy-preserving alternatives as defence and implementing a proof-of-concept API to be used as a prototype for privacy-preserving machine learning as a service.

To Apply

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:

Essential 

• 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, Machine Learning
• Demonstrated knowledge and skills in one or more of the following areas: machine learning, information theory, differential privacy, cryptography, game theory, probabilistic and statistical analysis
• 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, use of machine learning algorithms, development of efficient algorithms on large datasets, and development of security or privacy-preserving algorithms and protocols.
• 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.

Desirable 

• Previous experience or research in either theoretical frameworks for private machine learning, computational learning theory, or data-driven quantification and assessment of information leakage. 
• 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 dali.kaafar@mq.edu.au

Applications Close: Tuesday 4^th June 2019 at 11:59 pm AEST

Macquarie University is committed to Equity, Diversity and Inclusion. We value individual difference and recognise the strength of a vibrant, diverse and inclusive workforce where the backgrounds, perspectives and experiences of our staff are a driving force for collaboration, innovation and impact.

We work to ensure genuine equality of opportunity for people regardless of their gender, age, cultural background, sexual orientation, gender identity, disability and/or family status, and we encourage you to apply for a position at Macquarie University.