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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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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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Early- and mid-career researchers Other initiatives Education Academy school education programs Science videos and articles Immunisation, climate change and genetic modification History of Australian
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the academic promotions process. About You Completion or near-completion of Ph.D. in Genomics, Statistical Genomics, Quantitative Genetics, Computational Biology, or a related field. Expertise with genomic data
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degree research students Understanding of standard flow cytometry procedures Understanding of the fundamentals of bio foundry automation Experience with plant research (genetic engineering, molecular
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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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work. About you PhD in Neuroscience, Ophthalmology, Vision Sciences, or a related field experience working with iPSC-derived neuronal cultures and primary neurons experience with molecular genetics
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intersection of machine learning, crop genetics, and biological data science, contributing to high-impact research that supports accelerated crop improvement and strengthens Australia’s agricultural industries
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genomics, bioinformatics, computational biology, molecular ecology, molecular biology, or molecular genetics. Proven experience in designing and leading research projects, with a focus on the development
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, molecular biology, or molecular genetics. Proven experience in designing and leading research projects, with a focus on the development, optimisation, and application of genomic tools and technologies