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for Big Data Research in Health (CBDRH), strategically partnered with the School of Clinical Medicine (Women’s Health) at the University of New South Wales, Sydney (UNSW). This positioning places the NPESU
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most important summer cereal, producing large amounts of stem biomass with untapped potential for renewable energy and sustainable materials. In this role, you will explore genetic diversity in stem
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candidate will contribute to projects on flow-ecology relationships and habitat suitability modelling for freshwater organisms and will be comfortable working with large datasets, including spatial
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working with large datasets, including spatial information, hydrologic data and survey records. Skills and Experience To be considered for this position, you will have: completed a PhD or equivalent
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the application of analytic techniques to longitudinal or large mental health data sets or biobanks a strong applied research orientation with a proven ability to build successful working relationships with a
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coordination with the IDEA Bio team. Perform cultivation of microorganisms (yeast) using existing and refined the fermentation strategies. Deliver high-quality data to clients using fermentation workflows. Train
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to summarise or search in large quantities of information preferred. Aged Care Research & Industry Innovation Australia (ARIIA) continues to transform the way we care for Older Australians. Funded by
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 5 days ago
& upskilling opportunities . For more information on a range of lifestyle, financial and non-financial rewards and programs, please click here . To see what the Science at ANU community is like, we invite you to
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by the supervisor This is a research focused position. Further information can be found by viewing UQ’s Criteria for Academic Performance. About UQ Join UQ, a globally renowned institution fostering a
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and data interoperability challenges in an applied environmental field, experience working with environmental/hydrological data Demonstrated experience working with Generative AI and Large Language