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these constraints into the training objective, complicating model training. This project aims to leverage advancements in computer vision, particularly in implicit neural representations, to embed priors in neural
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learning. This program allows students to conduct cutting-edge AI research at a world-class institute and provides travel funding to gain valuable experience working with international collaborators in
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; be enrolled in a PhD program in the Faculty of Sciences, Engineering and Technology in the area of South Australian Quaternary Geology; and be undertaking a research project that includes a fieldwork
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an Australian citizen, Australian permanent resident, New Zealand citizen, Permanent Humanitarian visa holder or international student; be enrolled in a Doctor of Philosophy (PhD) program at the University
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). No extensions shall be considered. Eligibility To be eligible for the Scholarships, applicants must be: Commencing a full-time Doctor of Philosophy program in engineering at the University of Adelaide
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research papers. Program overview The successful candidate will receive: Admission to a PhD program at the University of Adelaide; A University of Adelaide Research Scholarship for 3.75 years, paid
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semester 2, 2025. Applicants must be awarded a Research Training Program Scholarship or University of Adelaide Research Scholarship to be eligible for this supplementary scholarship. Stipend: The scholarship
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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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opportunity to contribute to cutting-edge research that has a real-world impact on the agricultural sector. The Analytics for the Australian Grain Industry (AAGI) Scholarship Program (AU node) is funded by
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. This project will use state of the art MRI sequences to characterise the morphology and composition of human joints for a cohort of people enrolled in a social running program, and subsequently phenotype