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. While applicants are not expected to meet all criteria, those who demonstrate more of the following attributes will be highly regarded: Strong foundation in AI models: A deep understanding of contemporary
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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to trick AI-based models, pay little attention to fake-normal data traffic generated by Generative Adversarial Networks (GAN). This PhD research will address a major vulnerability in AI based smart grids by
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instance learning and weak supervision / spatial transcriptomics models to individualise tumour type, associated biomarkers and genomic characteristics to high precision. The resulting multipurpose machine