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programming and data analysis. Interest in developing methods, algorithms or software. Evidence of publications in high-quality peer-reviewed journals. Excellent communication skills. Experience
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experience using Python machine learning and large language models. Experience in machine learning and NLP for automated misinformation detection, social media data scraping and analysis, and human annotation
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metapopulation and/or individual based models Knowledge of Bayesian methods, including Approximate Bayesian Computation Experience with big data analysis and HPC environments Knowledge of additional programming
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activities including project management, stakeholder engagement, data collection and analysis, and the development of written outputs for both community organisations and peer-reviewed journals. The Research
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palliative care quality initiatives globally, PCOC supports clinical services through robust data collection, analysis, and quality improvement tools, with the aim of enhancing care experiences and outcomes
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), clinical trials, disease surveillance, and the use of novel methods including Bayesian network, machine learning, social network analysis and dynamic data visualisation tools. Further information is
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, providing evidence-based analysis for determining force effectiveness. The applicant will work with other researchers and engineers in A/Prof Szabo’s team who share broad goals in modelling and simulation and
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using statistical analysis. Experience in project management and working on field projects in the parenting field, and/or experience in working on large scale projects using administrative data. Relevant
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required of the position. Undertake literature searches and reviews. Assist with the preparation of ethics and governance applications. Undertake data collection and preliminary analysis. Assist with
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an opportunity to work with the Bureau of Meteorology, applying advanced analysis and programming skills to operational weather data for forecasting at various time scales. Key responsibilities include independent