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PhD Scholarship Develop AI and machine learning models to guide real-time, personalised treatment of paediatric brain cancer using multiomics and clinical data, within the internationally
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applied mathematical modelling machine learning multi-fidelity modelling numerical methods. Demonstrated programming ability (MATLAB/Python/C++) and enthusiasm to learn PyTorch. Previous experience in one
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PhD Scholarship Opportunity - Processing intelligence for green metals using in situ X-ray characterisation and machine learning Job No.: 693787 Location: Clayton campus Employment Type: Full-time
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This PhD research aims to develop and evaluate explainable AI and machine-learning approaches for early detection, risk stratification and prognostic prediction of colorectal cancer, with a focus on
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) to improve cardiovascular risk assessment and prediction. Research Aim This PhD research aims to develop and evaluate AI and Machine Learning approaches for early prediction, risk stratification and prognostic
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for Artificial Intelligence (AI) and Machine Learning (ML) to support earlier and more personalised healthcare. Research Aim This PhD research aims to develop advanced AI and Machine Learning methods
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learning, or human-computer interaction would be advantageous. How to apply We are seeking expressions of interest from qualified domestic candidates who wish to apply for this PhD opportunity. This position
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data provides opportunities for advanced Machine Learning (ML) approaches. Research Aim This PhD research aims to develop advanced Machine Learning methods for prediction, risk stratification, clinical
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at developing methodological contributions at the intersection of computer vision, multimodal learning, predictive world models, embodied AI, and human-robot interaction. The candidate will work towards models
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PhD candidate will have: A strong background in computer science, artificial intelligence, machine learning, or a closely related field. A solid understanding of machine learning concepts, particularly