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Australia’s future change-makers and create a better tomorrow. Work that matters We are seeking a Postdoctoral Research Fellow to contribute to the development of mathematical models to predict collective
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the Obstetrics unit providing supervision of clinical teaching to medical students across their obstetrics rotation, develop and coordinate O&G related SIM sessions and provide lectures and weekly tutorials
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at SAiGENCI, you will have ample professional, scientific and mentoring opportunities to assist in the continued development into a highly visible future leader in their own right. This opportunity encourages
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Ability to train and guide users in safe animal handling and facility procedures Our commitment to inclusion and diversity We are committed to fostering a culture of inclusion where diversity is celebrated
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community of staff are united by our purpose to inspire Australia’s future change-makers and create a better tomorrow. Work that matters Advance the frontier of AI by developing multi-agent systems capable
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forecasting/uncertainty. Holger Maier is internationally recognised for developing and applying AI/machine learning, optimisation (notably evolutionary algorithms), and decision-support methods for complex
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Australia’s future change-makers and create a better tomorrow. Work that matters Contribute to cutting-edge research in AI-enabled satellite autonomy, developing reinforcement learning solutions for real-time
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Range: $81,293 - $109,307 per annum (plus 17% superannuation) We are seeking a Research Fellow with experience in machine learning research and development, particularly with a specialisation in such
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lung health, across a range of laboratory and imaging programs. Role Summary This role will help to develop lung function-based respiratory biomarkers through AI, machine learning and image processing
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mechanisms of adaptive and acquired drug resistance, exploring network-level control and feedback in cell signaling systems, identifying novel drug targets and therapeutic strategies, and developing predictive