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opportunity to contribute to globally impactful research. About you Doctoral Qualification in Public Health or a relevant health discipline. Project Management Experience in large-scale research across
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Postdoctoral Research Associate in Global Environment Modelling of Soil Organic and Inorganic Carbon
or a related discipline, with an emphasis in numerical computation intermediate to advanced skills in large data analysis and manipulation, including programming in different languages including Matlab
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in the HARP trial. Ensure adherence to project timelines, budget, ethics approvals, reporting obligations, and data security and management requirements. Research Dissemination and Impact Drive
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Australian National University | Canberra, Australian Capital Territory | Australia | about 1 month ago
Position is an equal employment opportunity measure aiming to increase representation by the target group in accordance with the University Identified Positions Procedure For further information please
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. The project, "Building the bridge from GWAS to Breeder through multi-omic network data fusion", focuses on transforming GWAS discoveries into actionable breeding insights. Using sorghum as a model, the work
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, and may utilise iterative algorithms, machine learning and high-performance computing. Through the Monash Centre for Electron Microscopy, opportunities exist to acquire large experimental datasets using
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stability assessments and control development. You will: contribute to delivering the CfNETR project(s) in smart power system engineering; develop literature reviews and maintain data and knowledge
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of projects by managing and analysing data from clinical trials, cohort studies, and large linked administrative datasets. You will contribute to study design and implementation, perform statistical
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in expressing and purifying large multi-subunit protein complexes and analysing them through in vitro methods. Extensive experience in structural biology techniques, especially with cryo-EM
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will include leading and undertaking quantitative data analyses, including working with large-scale longitudinal survey and administration data, to generate novel insights and contribute to high-quality