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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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. Specific projects seeking applications are: Accelerating the discovery of inorganic solar-cell materials via a closed-loop, fully robotic synthesis–characterisation platform driven by multi-agent machine
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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
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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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microfluidic fabrication and experiments 3D printing machine learning. Demonstrated programming skills (Matlab, C++, or Python). Desired Demonstrated ability to work independently and to formulate and tackle
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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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(www.ledbyexperience.org) and network of collaborators in a recent review stated that societal issues of climate change, military conflict, and criminality, are inevitably connected with those of mental health and well
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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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" "Machine-learning-based imaging processing" webpage For further details or alternative opportunities, please contact: haoran.ren@monash.edu.