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team developing techno-economic analysis (TEA) frameworks for emerging precision-fermentation technologies. In this role, you will help shape the future of sustainable dairy by assessing how precision
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element discovery, engineered plant characterisation, and high-throughput screening of synthetic-biology constructs. Develop, optimise, and implement workflows for single-cell regulatory genomics assays
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combination between academic research and project/ stakeholder management, including the ability to switch between data collection and analysis, and developing proposals for continued collaboration and funding
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: Experience in physical system modelling including finite element modelling Experience working with large codebases in open source software environments Proficient user of HPC environments including MPI
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, you’ll have the opportunity to lead elements of major longitudinal and qualitative studies, collaborate with clinical and community partners, and contribute to publications and funding applications
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fundamental and demand-driven research on modelling and analysis of complex social networks. This line of research is broadly focused on modelling, analysis and estimation of complex network models in
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molecular synbio technologies. Ability to design, optimise and troubleshoot molecular workflows, including promoter/element selection, construct assembly, and functional validation. Demonstrated experience
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the execution of research activities focused on understanding the molecular mechanisms involved in Alzheimer’s disease. You will perform laboratory experiments, manage data analysis and collaborate with a broader
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% superannuation About the opportunity This role contributes to cutting-edge research in immunology, microbiome and nutritional analysis, and bioinformatics. It sits within a multidisciplinary team at the Nepean
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, facilitating continuous improvements to mental health services for the benefit of young people in Australia. Your key responsibilities will be to: undertake analysis of clinical, biological, and behavioural data