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the world. Ideal applicants will have a solid background in AI, machine learning, control theory or quantitative finance. Applicants with advanced programming skills (Python/C++); and a desire to publish in
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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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future autonomous instrument control and self-directed experimentation will be developed, recognizing the challenge presented by the integration of multiple complex systems. Coding and user interface
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and expertise and to contribute broadly to the goals of improving Victorian MCH service delivery. For example, project ideas may include: Models of Relational and Continuity of Care in MCH Contemporary
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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