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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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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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will likely have the following skills and experience: A PhD or master’s degree (or commensurate qualification/research experience) in Computer Science, Data Science, Forensic Science, Electrical
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. The role involves contributing to a major industry-aligned project funded by the Australian Government through the Australian Research Council’s Industrial Transformation Research Programme. This position
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to meet deadlines and effectively manage varying workloads and respond to changing priorities as required Demonstrated high level of communication skills Demonstrated hands-on experience in interface
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high-impact research at the interface of seafood safety, regulation, and public health Full time, ongoing role based in Hobart About the opportunity This is a senior, research-intensive position within
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program, including data stewardship, methodological innovation, quality assurance, and research initiatives. What we’re looking for: A PhD or equivalent in a relevant field. Demonstrated expertise