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world models with deep learning methods. World models are generative models that predict future outcomes given past ones. We aim to work with both images and audio modalities and be able to use the world
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Join us in advancing the frontier of plant sciences and making a tangible impact on agricultural resilience through the power of machine learning! We are seeking a highly motivated PhD candidate
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, natural language processing, and deep learning, will explore how fine-grained supervision signals and a new construction paradigm can improve the faithfulness and interpretability of dense and learned
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imaging analytics of muscle asymmetry, fat infiltration, oedema and scaring. Use deep learning to deliver automatic injury detection methodologies to reduce false negative assessments. Explore
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Match Officials Limited. This project aims to develop deep insights into the spatiotemporal characteristics of soccer match officials’ movement and positioning in the context of decision-making
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the assembly of the vertebrate body plan. There is particular focus on the deep part of the vertebrate family tree and correspondingly the early fossil history of the group, from the origin of vertebrates up
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Professor Bruno David of Monash University. These PhD projects will be part of the broader ARC project that aims to investigate the deep-time Aboriginal occupation of the limestone country of the Buchan
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you to apply. Your application will receive fair consideration. Challenge. Change. Impact! From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to
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for the power plant. We have an opening for a candidate with an interest in the application of machine learning to particle physics simulation and proven skills in software development. The student would
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This is a research opportunity for PhD students who are interested in learning satellite tracking (radar and laser) technology, Earth's gravity field variations, and climate changes by hydrological