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The Postdoctoral Fellow in Bayesian Computation will support the development of statistical methods based on Bayesian recalibration techniques using flexible transforms of surrogate models. These
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within experimental enclosures with the ultimate aim of reconstructing the visual circumstances leading up to mate detection. The successful candidate will contribute to an Australian Research Council
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biological and medical research questions. Strong expertise in (Bayesian) statistics and data science Experience with mathematical modelling (e.g., linear algebra, linear models methodologies
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and medical research questions. Strong expertise in (Bayesian) statistics and data science Experience with mathematical modelling (e.g., linear algebra, linear models methodologies) Demonstrated
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detection and monitoring, invariant and distributionally robust representation learning algorithms, and deployment-time calibration with uncertainty quantification using approaches such as conformal
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detection and AI-enabled forensic analysis, maintaining high-quality evidence databases and workflows. Supervision and Researcher Development: Develop an emerging research profile through high-quality
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researchers are advancing discoveries into practical health outcomes, including through a next-generation ovarian cancer screening trial designed to improve early detection . This reflects the visionary
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techniques for inverter-based resource dominated power systems, including mode identification, source detection, dynamic event classification, hardware-in-the-loop validation, research publication, and
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Connections in Cancer Care and Prevention (CASE) project, a newly established initiative focused on improving health literacy and access to cancer prevention, early detection, care and treatment for
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underwater camera configurations for AI detection of sea lice, wounds and individual fish identification via skin/spot pattern. The postholder will lead the development of behavioural welfare