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and machine learning analyses to uncover trajectories and predictors in young people. You will contribute to high-impact publications and global collaborations across NIH, MRFF and CRE-funded projects
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PhD in Computer Science, Robotics, Electrical Engineering or a related discipline. Expertise in Artificial Intelligence (AI), robotics and Internet of Things (IoT) technologies. Experience in embedded
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particularly interested in: machine learning for molecular and omics data, including representation learning for biological sequences and structures, and the integration of multiple omics layers machine
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Faculty of Engineering, Architecture and Information Technology / School of Electrical Engineering and Computer Science Full-time fixed-term position through to end of September 2029 Base salary will
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effectively within a multidisciplinary research environment. Experience with quantitative genetics, Bayesian methods, machine learning, large-scale genomic datasets, single-cell omics or integrative
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conclusion of the common first year: Aerospace engineering Chemical engineering Civil engineering Electrical and computer systems engineering Environmental engineering Materials engineering
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apply mixed-model statistical methodology, including genomic prediction, crop simulation and machine learning, to improve prediction of crop yield and related traits. Supervision and Researcher
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management systems, workflows and research infrastructure. Apply advanced statistical, machine learning and data engineering methodologies to large-scale, longitudinal datasets, contributing to
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: Bachelor of Engineering (Honours) Bachelor of Engineering (Honours) (Professional) studying one of the following majors: Electrical and Electronic Robotics and Mechatronics Mechanical. studying on
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the School of Chemical and Biomedical Engineering and the School of Electrical, Mechanical and Infrastructure will be considered. Conditions Recipients must agree to the University sharing their