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demonstrated proficiency in qualitative and/or multivariate quantitative research methods and analysis, have experience in supporting the management of a large research program, and have demonstrated an ability
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or knowledge of invertebrates within southern Australian agricultural systems Experience with molecular methods for species identification and/or population genetics. Knowledge of statistical analysis, data
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Institute for Machine Learning – the largest computer vision and machine learning research group in Australia – and contribute to world-leading research projects at the Centre for Augmented Reasoning
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. Very good organisational and management skills. Advanced analytic and computational skills, including the demonstrated ability to perform numerical and symbolic calculations. Senior Lecturer (Level C
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Health and Medical Sciences building on North Terrace. This role is critical to the delivery of the Human Biology and Biodental sciences curriculum for the Bachelor of Dental Surgery Program (BDS) and
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responders and operational risk assessment regarding skin decontamination and will build on a program of work focused on dermal exposure to chemicals. To be successful you will need: Completion of a PhD in
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experiments and take an active role in advancing the statistical methods employed at the Plant Accelerator® . The appointed individual will support plant scientists using our services to address a diverse range
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metapopulation and/or individual based models Knowledge of Bayesian methods, including Approximate Bayesian Computation Experience with big data analysis and HPC environments Knowledge of additional programming
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government and industries in South Australia, and overseeing Centre performance. The appointee will also be supported to establish and build a dynamic research program in machine learning or artificial
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upcycling of spent metal oxide cathodes, particularly, high Ni-containing oxides, through chemical-mechanical approaches, ionothermal/molten salt methods, etc. Project 2 (2 PhD students): Direct Recycling