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project management skills, and the ability to prioritise work, work to deadlines and undertake multiple parallel projects Demonstrated ability to identify, assess, test and evaluate technical applications
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, Computational Biology, or a related field. Strong experience with Python, R, or C++ programming and high-performance computing (GPU/parallel workflows). A research track record including publications
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of Earth and Planetary Sciences (EPS), and across schools in Curtin University. The applicant will work in parallel with the Director of Curtin’s Western Australia Organic and Isotope Geochemistry Centre (WA
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Testing, Parallel Payroll Testing, and User Acceptance Testing. Work closely with the Program Test Manager, Senior Functional Business Analyst, and other stakeholders to translate business requirements into
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or field including associated analysis possibly involving statistical or data analytical software. Work across teams and projects, often on a number of parallel and competing tasks. Work with discretion
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strengthening research capabilities in the region. The candidate will be part of the WAARC Postgraduate Cohort and supported through WAARC’s Postgraduate Research Scholarship Program. The candidate will work
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of Earth and Planetary Sciences (EPS), and across schools in Curtin University. The applicant will work in parallel with the Director of Curtin’s Western Australia Organic and Isotope Geochemistry Centre (WA
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of Earth and Planetary Sciences (EPS), and across schools in Curtin University. The applicant will work in parallel with the Director of Curtin’s Western Australia Organic and Isotope Geochemistry Centre (WA
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function via microbiota-gut-brain interactions. In a parallel program of research, we have been exploring epigenetic inheritance via the paternal lineage. We have discovered the transgenerational effects
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anomalies in evolving graphs. In this research proposal, our aim is to explore the parallels of deep learning and anomaly detection in dynamic graphs. In particular we are interested to redesign deep neural