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The Bob Croser Woodland Recovery Supplementary Scholarships are funded by the Bob Croser Woodland Recovery Project to support full-time PhD students who are commencing research to support woodland
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experience in managing complex projects and competing demands. Ability to operate complex infrastructure and bespoke software, including troubleshooting. Exceptional attention to detail and demonstrated
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group of PhD researchers who will tackle the most pressing questions in Machine Learning while ensuring AI serves humanity responsibly. You'll work within one of our specialised research themes, each
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eligibility for AHPRA registration Demonstrated experience in the conduct of tutorials, practical classes, demonstrations, workshops and clinical sessions Demonstrated experience in innovative teaching methods
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in administration, research, and teaching at an appropriate level Higher degree in research or teaching (MD or PhD) or working towards the same Proven experience in conducting high-quality research
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PhD in Computer Science, Engineering or other Machine Learning-related field. • Programming experience in python, C++ or other relevant language and experience in deep neural networks • Strong
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to developing research protocols, preparing manuscripts, and analysing data using statistical methods, turning results into meaningful insights. You’ll also have the chance to present findings through reports and
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: Postgraduate qualifications or progress towards postgraduate qualifications and extensive relevant experience; or PhD in plant science, genetics, physiology or biotechnology, or a substantially relevant
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. To be successful you will need: PhD or equivalent degree (or thesis submitted) in earth sciences. Demonstrated research ability in sedimentology and sedimentary geochemistry—preferably with expertise in
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successful you will need: A PhD in geology, geochemistry or a related field. An established track record of publication in isotope geochemistry and/or critical mineral ore systems. Demonstrated expertise in