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rankings including the QS World University Rankings 2026. Learn more about Monash . Today, we have the momentum to create the future we need for generations to come. Accelerate your change here. Monash
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analytical and problem-solving abilities, advanced computer skills across Microsoft Office and Google Workspace, and experience developing effective administrative processes will be essential. Familiarity with
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language processing, large language models, machine learning, network analysis, social media analytics, and large-scale analysis of online discourse and communities. This PhD scholarship will be based within
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algorithms for inverse molecular design. High-impact publications in premier machine learning conferences (e.g., ICML, NeurIPS, ICLR) and leading interdisciplinary journals at the intersection of AI and
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of Machine Learning as the problem of approximating function f from the pair of measurements (x,y), and Optimization as the problem of finding the value of input x that maximizes the output y given
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datasets is essential. Well-developed skills in machine learning approaches, clustering techniques and longitudinal modelling will also be highly regarded. We warmly invite applications for this exciting
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Multimodal AI and Machine Learning for Diabetes-Related Complications: Integrating Clinical Prediction, Decision Support and Longitudinal Risk Forecasting for Diabetic Foot Disease and Lower-Limb Amputation
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limited to optimisation, scientific machine learning and AI for science, numerical mathematics, inverse problems and scientific computing. The successful candidate will demonstrate expertise in the design
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MML for well-behaved models, and has been successfully applied to diverse problems including hypothesis testing, clustering, and machine learning. Aim 1: Theoretical Investigation of MML Properties
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they bond in materials, but also develop transferable skills in scientific computing, data analysis and visualisation. "Machine learning for atomic-scale structure determination in thick nanostructures" (with