410 phd-studenship-in-computer-vision-and-machine-learning PhD positions in Australia
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PhD Scholarship in History Job No.: 678754 Location: Clayton campus Employment Type: Full-time Duration: 3.5-year fixed-term appointment Remuneration: The successful applicant will receive a
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operation under reactive capture conditions. Unravelling reaction mechanisms and catalyst structure-performance relationships using advanced characterisation techniques and computational tools. Collaborating
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the following knowledge and/or experience are highly preferred: Computer Vision, Signal Processing, Machine Learning knowledge and/or; Experience Industry knowledge and/or; A track record of published
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with digital twin modelling, remote sensing, and cloud computing is valued, as is a commitment to learning and advancing in these areas. The successful candidate will have the ability to work with large
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participating university PhD admission requirements. c) Meet university English language requirements. d) Not have previously completed a PhD. e) Be able to commence the Program in the year of the offer. f) Enrol
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The CSIRO Industry PhD Program is a four-year research training program, focusing on applied research that benefits industry by solving real-world challenges. It aims to produce the next generation
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of the STAMP RSV Program, supported by the Stan Perron Charitable Foundation. The PhD candidate will play an important role in developing models of RSV transmission and vaccination efficacy to inform
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pioneering PhD project in partnership with ANCA, a world leader in CNC grinding machines and motion control systems. Supported by the prestigious Growth SUPRA PhD Scholarship, you'll join a dynamic research
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Applied mathematics, fluid mechanics, high-performance computer simulations. Full time, fixed term position (3 years) at Hawthorn campus $34,700 per annum (2025 rate) About the Scholarship Higher
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This PhD research scholarship (Learning Lessons from Drug Resistance to Tackle Herbicide Resistance) is funded by the Australian Research Council to support a full-time PhD student to undertake