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expertise in research methodology or willingness to learn. Well-developed computer skills. Application process Expressions of interest are invited to be submitted electronically to Professor Judith Finn via
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. Understanding of or curiosity about machine learning, AI, or cloud computing tools used in agricultural analytics. Interest or experience in working with industry, government, or multidisciplinary research teams
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study flow dynamics relevant to reactor design using optical diagnosing methods, followed by image processing, which may include machine learning-based techniques. This suits Mechanical Engineering
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Statistics for the Australian Grains Industry 3 (SAGI3). Investment. The University of Adelaide, in collaboration with Curtin University and The University of Queensland, is leveraging machine learning, data
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challenging for clinicians and pregnant women. Digital health records, advances in big data, machine learning and artificial intelligence methodologies, and novel data visualisation capabilities have opened up
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science technologies, and this is a perfect training opportunity for those who is interested in machine learning, data mining, artificial intelligence, and bioinformatics. High-performance computing may