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$85,555 - $116,094 p.a. (*PhD entry level $108,156 p.a.) plus 17% super Pioneer research in modelling heterogeneous populations through collaboration with leading institutions to advance mathematical
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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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approaches, including animal models of neurodegeneration, in vitro cell culture, pharmaceutical analysis and imaging modalities. This position offers the opportunity to collaborate with national and
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-care data is used to refine clinical practice and improve survival worldwide. This position offers the opportunity to: Develop and implement advanced data pipelines and predictive models using
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research program advancing carbon-neutral energy systems modelling for Australia's energy transition. This role focuses on the development and application of advanced forecasting and scenario analysis
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opportunity The University of Sydney is seeking a Postdoctoral Research Associate/Fellow to join a flagship, industry-funded research program advancing carbon-neutral energy systems modelling for Australia’s
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modelling/software methods. We are seeking a creative and motivated Early Career Postdoctoral Research Fellow to join this team. This is a unique opportunity to take a lead role in eDNA modelling and software
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. About the Role We are seeking a Research Fellow to join a dynamic team investigating the neuroscience of ageing, using the model organism Caenorhabditis elegans. Under the guidance of Chief Investigator
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 1 day ago
, or mantle structure. Proficiency in waveform processing, programming (e.g. Python, ObsPy, SPECFEM), and forward or inverse modelling is essential, along with a record of high-quality publications and
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modeller to help lead a collaborative research programme between the University of Queensland and King Abdulla University of Science and Technology (KAUST) with Prof David Suggett. Our shared goal is to