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-team and contribute to a clinical trial research project of national significance for youth mental health. The project applies modern data science methods to build explainable and integrated machine
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data science methods to build explainable and integrated machine learning models that can be utilised by health services to make real-time, data-informed clinical decisions in youth mental health care
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external organisations. Applicants from a range of disciplines or fields will be considered, including electrical, electronics, computer systems or telecommunications engineering. If you're curious about
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factors involved in the onset and progression of dementia. Advanced computational methods, including bioinformatics pipelines and machine learning, will be employed to uncover putative biomarkers and
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, cultural history, social history, military history, the history of religion, health, politics, anthropology or trade, or other associated fields. The Flinders based supervision team have expertise in German
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publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data
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technologies, social structures, and networks. Effective C2 organisational systems are critical not only to military settings, but also to the operation of many civil domains, including emergency response
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external enrolment procedures. Selection criteria Demonstrated experience in programming and system development. Expertise in Python programming and data analysis. Experience developing Machine Learning
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for alternative analytical approaches for vaccine–antigen quantification. You will then learn current industry best practice methods involving ELISA assays and biosensor technology at Zoetis before developing and
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government background checks (allow for between 4 to 8 weeks) and complete any other CSIRO requirements. Selection criteria To be eligible applicants must: Have a basic understanding of machine learning