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contribution of 17% superannuation applies. Fixed-term, full-time position available for 2 years. We are seeking an ARC Grant Funded Researcher to focus on the computation of carbon based materials for clean
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Computer Science, Electrical Engineering, or a related field. A PhD is highly desirable; candidates with a master’s or bachelor’s degree must demonstrate equivalent research or industry experience. Strong
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agricultural research and innovation. Key Responsibilities: Conduct research in remote sensing, plant phenotyping, and computer vision, with a strong emphasis on multi-modal image processing. Develop and
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This PhD scholarship is funded by an Australian Research Council Industry Fellowship grant. It is a 3.5-year research training program. The ARC Industry Fellowship program aims to develop a strong
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award, applicants must: be an Australian citizen, Australian permanent resident, New Zealand citizen, or a Permanent Humanitarian visa holder. be enrolled in a PhD or Master of Philosophy program in
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the EEE discipline: Information Systems, Control, Autonomous Systems, and Computer Engineering: Information systems and science, communications, control and dynamics, robotics and automation, artificial
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, or international student; be enrolled in a PhD program in the Faculty of Health and Medical Sciences the field of medicine known as nuclear medicine; or a field of academic study where a substantial component of the
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. Eligibility: To hold the award, applicants must: be an Australian citizen or Australian permanent resident be enrolled in a PhD program or Master of Philosophy, undertaking research in the area/s of obstetrics
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to assess the reliability of existing modeling tools by comparing them with experimental results. The objectives of this industry PhD program also include an internship at the industry partner site to join
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& Wine. This position will be responsible for effectively managing administrative activities associated with a major Commonwealth Government funded project under the Climate-Smart Agriculture program