Project

Energy aware and secure/trusted embedded intelligent processing is vital for systems where embedding devices with local processing capability is important for processing data and feature-driven learning in intelligent IoT and vehicular systems (e.g., autonomous vehicles). Different approaches can be used for hardware implementation from traditional microcontrollers to new approaches using GPU and reconfigurable FPGA technologies. This research aims to design and develop core algorithms and architectures for AI, IoT and Blockchain device analytics that are able to be effectively deployed into various hardware technologies by evaluating the speed, performance, and latency through hardware acceleration. The specific research topic can be discussed between the student and supervisory team, though an expectation is that an outcome of the research will be a Blockchain-enabled Intelligent IoT Architecture. Applications for smart cities, environmental sensing, communications, transportation, power systems, etc. can also be considered.

Ideal Candidate

This scholarship is for a PhD in the School of Science, Technology and Engineering in the area of "Embedded Intelligence - AI, IoT and Blockchain Device Analytics for Efficient Hardware Implementation". This opportunity will suit a person who has a strong work ethic, is self-motivated, and has a desire to learn and develop as a researcher. Applicants with experience in the research area (AI, IoT, Blockchain, etc.) and practical hardware development skills (e.g., FPGA, GPU, LabVIEW, etc) will be strongly looked upon.

Contact Person

For questions or to submit your Expression of Interest, please contact Prof. Li-minn Ang (Kenneth) at email: lang@usc.edu.au

Eligibility

• Be accepted into the Doctor of Philosophy program at the University of the Sunshine Coast
• Not have an equivalent qualification to the one for which is currently being applied for
• Have a First-Class Bachelor Honours Degree, or show equivalent level of achievement with other academic qualifications or professional research experience

Selection criteria

Standard Criteria

• Academic Achievement (Assess the quality of the candidate's academic performance)
• Research Capability (Assess evidence of research preparedness and capability)

Project Specific Criteria

• Experience in the research area (AI, IoT, Blockchain, etc.) and practical hardware development skills (e.g., FPGA, GPU, LabVIEW, etc).

Application

This will be a two-stage application process:

Stage 1 - Expression of Interest:

• Interested applicants should email their Expression of Interest (EOI) together with any supporting documents to the contact person.
• The scholarship panel will review the EOI. If shortlisted, you will be invited for interview.
• The preferred applicant will then be invited to formally apply for HDR program and scholarship.

Stage 2 - Formal application (only if you have been invited to apply)

• Read the important information on How to Apply for a HDR Program at USC.
• Download and complete the USC Research Scholarship (USCRS) application form.
• Attach your completed USCRS application form as a supporting document to your online HDR Program application.

*scholarship offer is subject to applicant meeting the eligibility requirements for entry into a higher degree by research program at USC. You will not receive an offer for Scholarship if you have not been accepted into the program.

If you require assistance on how to apply, contact the Graduate Research School by email researchtraining@usc.edu.au