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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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Grant and offers excellent training in experimental techniques, data analysis, and translational research. The successful candidate will gain in-depth expertise in both cardiovascular and neurological
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applications in timing and biology, quantum circuits and quantum computing. Projects will be available at the University of Adelaide, RMIT and the University of Queensland. Eligibility: Applicants must be
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they bond in materials, but also develop transferable skills in scientific computing, data analysis and visualisation. "Machine learning for atomic-scale structure determination in thick nanostructures" (with
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science technologies, and this is a perfect training opportunity for those who is interested in machine learning, data mining, artificial intelligence, and bioinformatics. High-performance computing may