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                Mathematics, Data Science, Computer Science Engineering, Artificial Intelligence, and Information Technology will also be considered, but it will further be required that they also have a strong interest in 
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                Antenna Design: Developing innovative antenna systems compatible with metal detector coils, optimized for tasks such as minimum-metal landmine detection and deep object detection. Low Power, Compact 
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                applicant will receive a tax-free stipend, at the current value of $36,063 per annum 2025 full-time rate, as per the Monash Research Training Program (RTP) Stipend www.monash.edu/study/fees-scholarships 
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                environments. Access proprietary market data and institutional infrastructure, including cutting-edge computing environments and live market simulation tools. Translate research into production, contributing 
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                , in the Faculty of Business & Law at Curtin University, is seeking one (1) doctoral applicant (PhD) to join an Australian Research Council [ARC] Discovery Project, namely: Optimizing Benefits 
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                the optimal habitat reconstruction for declining bird species, how to best engage community and landholders in the recovery effort, and priority species-specific objectives for guiding restoration actions and 
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                significant research program funded by the Australian Research Council Discovery Project titled “Discovering the sustainable size of cities”. This interdisciplinary project investigates how high-speed rail (HSR 
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                -temperature performance. The PhD project will focus on the development, investigations and optimizations of new electrode and electrolyte materials. The project will expand the student’s skill set in scientific research 
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                investigate the optimal methods for combining multi-satellite InSAR with a network of Kurloo GNSS devices to provide robust 3D ground motion monitoring from space. The potential benefits may include 
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                to: - Developing underwater communication systems using deep learning which are well-performing to nonlinear channels. - Establishing a deep learning architecture which is optimal for underwater acoustic