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Research Fellow – AI/Machine Learning in Pharmaceutical Data Job No.: 697007 Location: Clayton campus Employment Type: Full-time Duration: 11-month fixed-term appointment Remuneration: $86,195
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passion for applying advanced machine learning to real-world medical challenges. If you thrive in collaborative, multi-disciplinary environments and possess a strong technical foundation in AI methodologies
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, privacy-preserving technologies, adversarial machine learning, explainable AI, or secure software engineering. Collaborate and Translate: Work within a supportive team, present findings at national and
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materials discovery with cutting-edge high-throughput platforms, robotics, machine learning, and autonomous experimental workflows. Access World-Class Facilities: Based in the Department of Chemical and
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We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis. This is a unique opportunity to
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, data processing pipelines, machine learning and generative AI applied to physical activity and sleep research. The position will contribute to the development of an AI-based behaviour change tool and
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neurocritical care research The Opportunity We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis
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. The successful candidate must hold a PhD in particle physics or a closely related discipline. This is an exciting opportunity to develop your research expertise, collaborate within a leading particle physics
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capture how a dense fluid migrates, spreads and becomes trapped within a deformable, yield-stress material. Working alongside a co-supervised PhD student and the wider investigator team, you will build and
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activity. The probes to be developed will utilise a quantum sensor based on optically detectable defects in diamond that are sensitive to magnetic fields. To be appointable into this role you will hold a PhD