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Australian National University | Canberra, Australian Capital Territory | Australia | about 3 hours ago
The ANU Mathematical Sciences Institute is seeking to appoint up to two PhD candidates in geometric analysis. Position overviewThe candidates will be supported by scholarships funded through an
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Primary supervisor David Dowe Co-supervisors Paul Lasky Kendall Ackley Research area Data Science and Artificial Intelligence The recent discovery in 2015 of gravitational waves from colliding black
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Primary supervisor David Dowe Co-supervisors Paul Lasky Kendall Ackley Research area Data Science and Artificial Intelligence The recent discovery in 2015 of gravitational waves from colliding black
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. Novel Adversarial Machine Learning algorithms for structured data will be proposed. The algorithms will be further extended to graph-structured data. Applications of AML will also be investigated to
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. Novel Adversarial Machine Learning algorithms for structured data will be proposed. The algorithms will be further extended to graph-structured data. Applications of AML will also be investigated to
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Overview Title PhD Scholarship: A Vision-Based Approach to Biofouling Analysis using Deep Learning Techniques College College of Science and Engineering Opening date 23-09-2026 Closing date 13-11
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datasets to train effectively. In practice, acquiring high-quality spectral data from wet-lab experiments is expensive and time-consuming. Furthermore, relying on a single spectral modality often
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datasets to train effectively. In practice, acquiring high-quality spectral data from wet-lab experiments is expensive and time-consuming. Furthermore, relying on a single spectral modality often
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Skip to content Next Generation Graduates Program - Sports Data Science Scholarships (Honours, Masters and PhD) Future student scholarship Scholarship details Study levels Student type Future
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performance metrics and key performance indicators (KPIs) to determine influential statistics for team and player performance, using league-wide data. The work will include opposition and team analysis