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their best work. THIS ROLE IS LOCATED IN SYDNEY, AUSTRALIA. The School of Mathematics and Statistics currently has more than eighty continuing academic staff and more than thirty research staff as
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Full time, 2-year fixed term opportunity, located at the School of Mathematics and Statistics on the Camperdown Campus Opportunity to contribute to research on hybrid numerical-exponential
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School of Mathematics and Physics Full-time, fixed-term position for up to 2 years Base salary will be in the range of $82,057.75 - $109,246.18 + 17% Superannuation (Academic Level A) Based at our
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users, researchers, and developers, both internally at the University of Sydney and externally across multiple institutions publish research papers on mathematical theory and the development and analysis
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at the University of Sydney and externally across multiple institutions publish research papers on mathematical theory and the development and analysis of algorithms compile data sets relevant to research in
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at traditional domains (applied mathematics, data science, systems and control theory), multidisciplinary journals for a broad scientific audience, as well as discipline-specific journals in other domains (e.g
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Australian National University | Canberra, Australian Capital Territory | Australia | about 2 months ago
at the John Curtin School of Medical Research (JCSMR), within the ANU College of Science and Medicine. This role will lead the development of advanced deep learning frameworks—including graph neural networks
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/engineering/our-schools/chemical-engineering Skills & Experience PhD in Engineering or Mathematics. Demonstrated skills and experience with process control and modern control theories including nonlinear
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27 Oct 2025 Job Information Organisation/Company UNIVERSITY OF MELBOURNE Research Field Mathematics Researcher Profile First Stage Researcher (R1) Country Australia Application Deadline 25 Nov 2025
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the WATOC Dirac Medal. As the successful candidate, you will contribute to the design and implementation of AI models that integrate quantum mechanical theory with deep learning, enabling rapid and