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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 27 days ago
processing, computer programming, and fieldwork are encouraged to apply. The successful candidate will be a member of the Geophysics Department based at RSES. RSES is Australia’s leading academic research
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Innovations Group seeks a forward‑thinking expert in statistical machine learning to translate complex biological datasets into actionable AI‑driven insights. You will enhance genomic selection and breeding
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developing research projects and reporting against milestones. Experience working with a range of computer systems and applications, including referencing software (e.g. EndNote), survey platforms and high
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Earth Engine, ENVI, MATLAB, or R. Desirable Proficiency in applying machine learning methods to multispectral and hyperspectral data for detecting crop diseases and estimating crop yield and quality
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manufacturing principles. Experience with machine learning methods and integration into hybrid modelling systems Demonstrated ability to clearly communicate research concepts and results in high-quality journal
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experience in using statistical and mathematical tools to analyse and interpret soil data, spatial modelling, multivariate statistics and/or machine learning, and relevant coding languages (e.g. R, Python
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machine learning to create improved reconstructions of the ice sheet. This role is based in Hobart, Tasmania and visa sponsorship and relocation allowances may be considered for the right candidate. What
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Intelligence or Machine Learning, with demonstrable analytical skills. Excellent research record evidenced by first-author publications in strong international journals and conferences. Proven experience in
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Intelligence or Machine Learning, with demonstrable analytical skills. Excellent research record evidenced by first-author publications in strong international journals and conferences. Proven experience in