255 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" "St" "St" Fellowship positions in Australia
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econometrics and machine learning, is highly desirable. You are well-organised and capable of managing multiple tasks to meet deadlines, with excellent written and verbal communication skills for producing clear
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discover them The Opportunity The Department of Electrical and Computer Systems Engineering at Monash University is seeking a motivated Level A Research Fellow for a 2 year research-only appointment. A Level
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
machine-learning methods to investigate the deep-time controls on copper mineralisation. The role will involve developing reproducible computational workflows, generating predictive maps of copper
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. This pivotal role sits at the heart of the Strategic Alliance between Open Door and Military and Emergency Services Health Australia (MESHA), strengthening national research capability and driving meaningful
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 5 days ago
: PD & PEWER Level B Research Fellow_SOE.pdf Work with world-leading researchers in robotics, computer vision, and systems and control Contribute to impactful research on cutting-edge event-based sensing
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systems (such as RedCAP), Endnote files, and databases Demonstrated experience with data analysis, visualization, and building machine learning models in programming language such as Python or/and R
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completion) in computer science, electrical engineering, AI, machine learning, remote sensing, robotics, or a closely related discipline. Demonstrated expertise and research track record in deep learning and
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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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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