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Science and Health laboratory to work on a Defence project related to risk-based decision making for skin decontamination in emergency response incidents. Dermal exposure is an important secondary route
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available for passionate and early career Researcher to join our team within the College of Science and Engineering as a Postdoctoral Research Fellow, Population Genomics. Full-time; fixed term to July 2027
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collaboration between industry, government, and academia. The Australian Institute for Machine Learning (AIML) at the University of Adelaide is the largest computer vision and machine learning research group in
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and social determinants influencing sexual health outcomes. You will oversee both qualitative and quantitative data collection, ensuring cultural safety and community governance, while driving knowledge
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hearing care. This role supports a high-impact research program focused on addressing the unmet needs of adults with hearing loss through data-driven policy, service innovation, and community-based
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projects including complex data analysis (e.g., telemetry or genetic data) and paper writing The candidate will be working remotely (i.e. off-campus) providing excellent work flexibility Position Overview
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or data to inform research outcomes. Proven skills in study design and data collection methods, including development of in-person data collection tools (such as surveys and interview schedules) and
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are looking for a highly motivated and collaborative researcher who holds a PhD in molecular biology, immunology, cancer biology, or a related discipline. The ideal candidate will have demonstrated expertise in
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, mineralogical, geochemical and structural data) and methodologies, with applications to the mineral industry. Working in collaboration with researchers from Earth and Physical Sciences, Engineering, CSIRO
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for (Selection Criteria): Essential: A doctoral qualification in a relevant engineering, computing, or physical sciences discipline. Demonstrated research expertise in data analytics, machine learning, artificial