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university research into commercial outcomes. Under this program, PhD students will gain unique skills to focus on impact-driven research. This Project aims to develop a predictive machine learning model
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-Height Ratio (KBR) have shown promise in predicting patient outcomes. While skeletal muscle measurements like PMD are valuable, the inclusion of organ metrics such as KBR suggests a comprehensive approach
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analysis and data processing. Strong programming skills in R (preferable) and/or Python, and experience or interest in weather prediction or climate models. Knowledge of machine learning, AI techniques, and
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and children's observed birth events and their actual health and well-being outcomes. The latest machine learning and artificial intelligence advancements can mine these datasets to create prediction
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) implement the COMPAS survey across two waves at St John Ambulance, (c) develop a predictive algorithm that can predict suicidal intentions and behaviours 12 months later, (c) use the algorithm to stratify
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prediction, signal tracking, fluid dynamics, and space exploration. Advancing Signal Modelling with Physics-Informed Neural Networks This project aims to develop Physics Informed Neural Networks (PINNs
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, causing poor rates of asymmetric redox reactions or poor ability to detect chiral analytes. Chirality is as powerful as it is elusive: we do not have accurate models to explain and predict, especially
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-learning models, improve the prediction of treatment outcomes, and promote responsible data sharing. The successful applicant will join a supportive and collaborative team based at Flinders University
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) to simulate sewer/stormwater system behaviour, predict risks, and optimize interventions. GNNs act as surrogate digital twins, embedding hydraulic principles to model how land-use changes and extreme weather
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will aim to develop novel tools to aid surgical fixation or predict complications and outcomes. Each PhD student will be expected to develop innovative solutions to the problem and publish approx. 3-4