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Acknowledgement of Country CSIRO acknowledges the Traditional Owners of the land, sea and waters, of the area that we live and work on across Australia. We acknowledge their continuing connection to their culture and pay our respects to their Elders past and present. View our vision towards...
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Acknowledgement of Country CSIRO acknowledges the Traditional Owners of the land, sea and waters, of the area that we live and work on across Australia. We acknowledge their continuing connection to their culture and pay our respects to their Elders past and present. View our vision towards...
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Acknowledgement of Country CSIRO acknowledges the Traditional Owners of the land, sea and waters, of the area that we live and work on across Australia. We acknowledge their continuing connection to their culture and pay our respects to their Elders past and present. View our vision towards...
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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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successful candidate, you will bring: Relevant tertiary degree, or equivalent relevant work experience, in Electrical Engineering, Mathematics or related fields, with a focus on power systems engineering
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, materials science, geology, geochemistry), mathematics, data science, and business. For information and contacts details please see the Mineral Resources Project List linked. Location: Various, AU (refer to
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bring: A PhD, or an equivalent combination of qualifications and demonstrated research experience, in Electrical Engineering, Mathematics or related fields, with a focus on power systems engineering