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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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Magma Research Associates / Magma Research Fellows to develop and maintain the Magma computer algebra system (http://magma.maths.usyd.edu.au/magma/ ). These positions are based at the University
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in robotics, machine learning, battery systems or a related discipline to deliver project outcomes, build productive research partnerships and contribute to high-quality outputs. You will have the
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your expertise in robotics, machine learning, battery systems or a related discipline to deliver project outcomes, build productive research partnerships and contribute to high-quality outputs. You will
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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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, 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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are particularly interested in: machine learning for molecular and omics data, including representation learning for biological sequences and structures, and the integration of multiple omics layers machine learning
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research infrastructure. Apply advanced statistical, machine learning and data engineering methodologies to large-scale, longitudinal datasets, contributing to innovative melanoma and skin cancer research
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, machine learning, and multi-omics technologies to drive discoveries that have the potential to transform cancer diagnosis, treatment, and patient outcomes. This is an exceptional opportunity to create
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. Knowledge of data-driven analytics, machine learning, signal processing, or advanced modelling techniques relevant to power systems. Experience with real-time simulation platforms, hardware-in-the-loop