University of Technology Sydney PhD Scholarship Opportunity

A fully funded PhD Scholarship is available for an outstanding candidate to work on a 3+ year PhD program at the University of Technology Sydney (UTS), Australia. The project is based within the Faculty of Engineering and IT (FEIT) and brings together a collaborative multidisciplinary research and development group comprising Bosch and UTS. The successful candidate will join a multi-disciplinary collaborative research team, to undertake independent scientific investigations and carry out associated tasks under the guidance of senior industry researchers and academics. Quality research with practical outcomes and publications in high impact journals and conferences will be expected.

Federated Learning (FL) is a modern approach for training machine learning models across multiple, decentralized systems, each holding local, potentially sensitive data. It is expected that a successful PhD candidate will work on “Privacy-preserving computing” and “Computing on Encrypted Data technologies”. In particular, Secure Multiparty Computation (MPC) to realize secure aggregation for FL. This work will require knowledge or a strong interest in modern cryptography, machine learning and knowledge in algorithmic hardware acceleration along with good programming and mathematics skills.

Scholarship

The scholarship is available to eligible domestic/international candidates to undertake 3+ year full-time Ph.D. program. The scholarships are comprised of a Tuition Fee Offset and a Living Allowance Stipend. The value and tenure of the scholarships is a full-time stipend rate of $28,854 per annum (2022 rate, indexed annually).

Expressions of Interest

Prospective applicants should submit an expression of interest by providing the following information by email to Justin Lipman: [Email Address Removed]

• 2-page CV
• Copies of your Academic Transcripts

We are seeking applicants with outstanding academic merit and prior research experience or good knowledge of modern cryptography and machine learning. To be competitive in winning a scholarship, you will need the following:

• A UTS-recognised master’s by research or an equivalent.
• Prior research background preferred.
• Publications in reputable international conferences or journals (highly regarded).
• Can communicate effectively in English and capable of technical writing in English.