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Synthetic data generation has drawn growing attention due to the lack of training data in many application domains. It is useful for privacy-concerned applications, e.g. digital health applications based on electronic medical records. It is also attractive for novel applications, e.g. multimodal...
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infancy is difficult. This PhD program aims at using state-of-the art multi-channel near infrared spectroscopy (NIRS) to assess the functional brain response of infants born preterm in long-term follow-up
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brain health. We are seeking a highly motivated Research Fellow to join a multidisciplinary and multi-institutional research program within the CDCO Academic Node. This role focuses on evaluating novel
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potential remedial approaches - will be explored in this research program and they include (as examples): variability in staining outcomes across different stains and different sites (even within a given
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I supervise a wide range of projects in stellar astrophysics, with a focus on low and intermediate-mass stars, which have masses similar to or slightly larger than our Sun. This work is carried out within the Centre of Excellence for Astrophysics in 3D: ASTRO 3D. As a member of my group, you...
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Domestic Student Recruitment and Engagement Manager Job No.: 690814 Location: Mulgrave Employment Type: Full-time Duration: Continuing appointment Remuneration: $120,138 - $132,610 pa HEW 8 plus 17% employer superannuation Amplify your impact at a world top 50 University Join our inclusive,...
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imaging centres in Australia, hosting many cutting-edge imaging equipment for biomedical imaging research. The Department of Data Science and AI, Faculty of IT is home to many world class research programs
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Future Fund–supported program (2026–2030) to strengthen evidence on addiction, self-harm and mental ill health. The multidisciplinary study will analyse 20 years of binational cohort and cross-sectional
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This PhD project is funded by a successful ARC Discovery Project grant: "Improving human reasoning with causal Bayesian networks: a user-centric, multimodal, interactive approach" and the successful applicant will work as part of a larger research team. Reasoning and decision making under...
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Anomaly detection is an important task in data mining. Traditionally most of the anomaly detection algorithms have been designed for ‘static’ datasets, in which all the observations are available at one time. In non-stationary environments on the other hand, the same algorithms cannot be applied...