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modelling, and resilience science. You will work within an interdisciplinary team, engage directly with communities, policymakers, and practitioners, and contribute to co-designed toolkits and guidelines
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Australia's national science agency, we solve the greatest challenges through innovative science and technology. We put the safety and wellbeing of our people above all else and earn trust everywhere because we
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from other quantitative disciplines – such as data science, mathematical statistics, actuarial science, public health, or psychology – who have strong quantitative skills and an interest in causal
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Doctor of Philosophy (PhD) on Phase Transformation in Green Steel Scholarship Opportunities at Faculty of Engineering Job No: 685999 Location: Clayton campus Employment Type: Full-time Graduate
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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open to candidates who wish to pursue a PhD on antisemitism using social science, media and communications, and/or other relevant interdisciplinary approaches. The successful applicant will be embedded
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. An additional amount of up to $5,000 is available to support project costs, equipment or research-related travel for site visits, data collection, and/or conference attendance. Eligibility To be eligible
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) and complete any other CSIRO requirements. Ideally, the applicant will have a bachelor degree in chemistry, chemical engineering, material science or engineering or relevant fields. Preference will be
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recently been awarded an Incorporating Patient Data in Health Technology Decision Making Grant under the 2025 Preventative and Public Health Research Initiative of the Medical Research Future Fund (MRFF
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between Queensland University of Technology (QUT) and the Queensland Women and Girls’ Health Promotion Program (QWGHP), we are offering a fully funded PhD scholarship for a motivated candidate to undertake