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: Research: Development and validation of predictive maintenance algorithms for solar farms. Interface with industry partners for knowledge sharing and feedback. Play a key role in reporting to the funding
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Australian National University | Canberra, Australian Capital Territory | Australia | about 2 months ago
postdoctoral researcher with: A PhD (or near completion) in Computer Science, Computational Biology, Mathematics, Bioinformatics, or a related discipline. Proven expertise in machine learning and algorithm
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distributions. Demonstrated experience in characterising changes in the chemical or physico-chemical properties of biological components (preferably food), as a result of physical, chemical or biological
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algorithms and methods for adaptive and personalised feedback, modelling learning behaviours with sequence and deep learning methods, and generating interpretable insights through novel analytics and
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experience. Experience in analysing large, complex ecological or biodiversity datasets. Strong proficiency in statistical modelling, including experience with species distribution models, community ecology
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of classical and hybrid classical-quantum algorithms for treating the correlations. This position offers exciting opportunities for collaboration within UQ, across the QDA network, and with external research
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. Harnessing technology, we thrive as a distributed yet connected community, welcoming and engaging with people across Australia and the world. Learn more about the Faculty of Science and Health here . Learn
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large-scale distributed computing systems (e.g. Edge, IoT), evidenced by involvement in several industry projects. Technical Experience: Exposure to Go, Python, Java or equivalent. Experience with
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on clusters and high-performance computing infrastructure), Information Retrieval methods, Machine Learning algorithms, wrangling large-scale datasets, and showcasing the research results. The ability to work
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into how the size, distribution, material aspirations and other characteristics of Australia’s population are likely to affect Australia. Closing date: Closed Conference funding Theo Murphy Initiative