183 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" Fellowship research jobs in Australia
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treatments for glaucoma and other optic nerve diseases that cause irreversible blindness. This position is a funded a Snow Vision Accelerator Postdoctoral Fellowship. Learn more about the Snow Vision
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within the Faculty of Engineering, currently with over 1500 students and 43 academic staff, with an operating budget of around $18 million. For further information about our School, please visit - https
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& generous leave options. Salary packing options + 17% Super. EAP, fitness passport & discounted private health. Where to apply Website https://www.timeshighereducation.com/unijobs/listing/405620/research
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Intelligence or Machine Learning, with demonstrable analytical skills. Excellent research record evidenced by first-author publications in strong international journals and conferences. Proven experience in
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pm Where to apply Website https://www.timeshighereducation.com/unijobs/listing/405562/postdoctoral-fellow… Requirements Additional Information Work Location(s) Number of offers available1Company
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opportunities for student supervision and career development. For more about the Fairlie Group please visit - https://imb.uq.edu.au/research-groups/fairlie . Key responsibilities will include: Research
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, rotating machines, system integration and electrical reticulation/protection. This role will also see you work collaboratively with a multidisciplinary team to advance renewable energy technology through
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, please contact Dani, v ia talentsupport@rmit.edu.au or visit our Careers page for more contact information - https://www.rmit.edu.au/careers . We are a Circle Back Initiative Employer – we commit
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. This pivotal role sits at the heart of the Strategic Alliance between Open Door and Military and Emergency Services Health Australia (MESHA), strengthening national research capability and driving meaningful
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 7 days ago
machine-learning methods to investigate the deep-time controls on copper mineralisation. The role will involve developing reproducible computational workflows, generating predictive maps of copper