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in Deep Learning Theory who has: a PhD in mathematics, applied mathematics, data science, or a related area an excellent track record of publishing high-quality papers on deep learning theory, machine
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Computer Sciences to contribute to the Schools teaching and learning outcomes in the Master of Computer Science. We are welcoming applicants with expertise in all areas of computer science, including
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partners and stakeholders use mechanistic modelling to spatialise crop yield predictions under a variety of data input scenarios use data-driven models and machine learning to better understand the spatio
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Machine Learning”). Working closely with Dr. Clement Canonne and his team, the successful candidate will develop and analyse new differentially private algorithms for distributed statistical inference, and
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critical, innovating at the boundaries of their disciplines and creating exciting and engaging learning experiences for our students – the global citizens of tomorrow. Design is a rapidly growing and highly
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) at the University of Sydney. The ACFR is one of Australia’s leading robotics research groups, and the Robotic Imaging Lab is focused on endowing machines with new ways of seeing the world. We are expanding our team
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collaborator with the aim to use machine learning/AI approaches in combination with commercial multispectral and hyperspectral remote sensing platforms to perform within-field mapping of weeds and disease in
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focused) who possesses: PhD in interaction design, human-computer interaction or cognate field sound experience of teaching and learning, and the ability to contribute to teaching at undergraduate, honours
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literacy with a good knowledge of relevant computer programs, and ability to work across and connect these as needed. Desirable criteria – you may have (or be willing to learn) the ability to write research
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thrives in a multifaceted environment. You will not only deliver a comprehensive curriculum encompassing software development, machine learning, computer systems, and networks, but also be instrumental in