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for mining and aerospace applications. This may interest scientists/engineers in fields such as physics, mathematics, computer science with experience in computer vision. The position is based in Brisbane, co
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This scholarship is jointly funded by a leading computer vision company in Australia and the STEM College of RMIT University. The research includes investigation into automated product quality
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"A picture is worth a thousands words"... or so the saying goes. How much information can we extract from an image of an insect on a flower? What species is the insect? What species is the flower? Where was the photograph taken? And at what time of the year? What time of the day? What was the...
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collaboration between industry, government, and academia. The Australian Institute for Machine Learning (AIML) at the University of Adelaide is the largest computer vision and machine learning research group in
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. The faculty encompasses two national schools, four distinguished research institutes, and specialised programs including the Western Civilisation Program. Reporting to the Provost, the position has
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Our dynamic ‘Digital Crops’ team is seeking an experienced and motivated Research Scientist, with a passion for applying emerging computer vision techniques for crops, to join their team in
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Exchange (EIX), this role is central to designing and delivering impactful programs such as the Educator Capability Program and the Swinburne Educator Academy. You’ll work closely with academic and
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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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Scholarship code: SRS-25032 This scholarship has been established thanks to the generosity and vision of the late Mr Anastassios Vassilogianis, benefactor of La Trobe University's Greek Studies
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approaches to model uncertainty for learned computer vision systems, including dense prediction. The position will develop novel methods for deep learning in computer vision that accurately quantify their own