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Antarctica’. Computational geophysics at the University of Tasmania spans applications to earth system physics, with a strong focus on geophysical data analysis, machine learning and inverse methods relating
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, and patient safety. In learning and teaching, the Faculty offers a unique suite of capability-based medical educational programs aimed a post-graduation subspecialty medical education and training, and
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experiences are valued, and where our people are empowered to thrive through supportive leadership, shared responsibility, and a deep commitment to genuine care and respect for our community. Find out more
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different backgrounds, identities, and experiences are valued, and where our people are empowered to thrive through supportive leadership, shared responsibility, and a deep commitment to genuine care and
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drone applications. We're a close-knit and ambitious team with deep technical expertise and a strong sense of purpose. We're hands-on, mission-oriented, and believe in building systems that matter - from
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, medicine, cardiovascular research) and significant research experience (10+ years). Deep knowledge of laboratory and animal research methodologies, including NHMRC ethics requirements. Demonstrated capacity
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, cooperative swarms, next-generation high-performance design, AI flight safety, and drone applications. We’re a close-knit and ambitious team with deep technical expertise and a strong sense of purpose. We’re
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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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team developing novel deep learning approaches with real-world impact in the space domain. This is an exciting opportunity for a motivated researcher to build on a strong academic publication record
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Academic Level B: Completion of a PhD in the field of Computer Science/Artificial Intelligence. Software engineering expertise, including design and implementation of AI-based models (machine learning, deep