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The University of Adelaide is seeking to appoint an academic research leader of international standing to join the Australian Institute for Machine Learning (AIML) as a Professorial Research Fellow
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completion) in computer science, electrical engineering, AI, machine learning, remote sensing, robotics, or a closely related discipline. Demonstrated expertise and research track record in deep learning and
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manufacturing principles. Experience with machine learning methods and integration into hybrid modelling systems Demonstrated ability to clearly communicate research concepts and results in high-quality journal
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Innovations Group seeks a forward‑thinking expert in statistical machine learning to translate complex biological datasets into actionable AI‑driven insights. You will enhance genomic selection and breeding
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focuses on scalable, AI-driven decision-making in collaboration with defence industry partners and an academic partner at the University of Melbourne. One role focuses on machine learning for decision
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at the University of Adelaide, contributing to cutting-edge research in computer vision and machine learning for space applications. This role focuses on advancing machine learning and computer vision research, with
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(e.g., Docker, Kubernetes, cloud/edge environments). Demonstrated expertise in AI, distributed computing, machine learning, or systems software design. Strong background in software engineering
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geometry, and/or data science. Specific topics of focus include, but are not limited to, linear response, random and nonautonomous dynamical systems, spectral analysis, machine learning, data-driven dynamics
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Computer Science, Applied Mathematics/Statistics, Robotics, Physics, or related discipline, with an excellent academic record. Demonstrated expertise in computer vision and machine learning, including object
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Computer Science, Applied Mathematics/Statistics, Robotics, Physics, or related discipline, with an excellent academic record. Demonstrated expertise and leadership in computer vision and machine learning research