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superannuation) Amplify your impact at a world top 50 University Join our inclusive, collaborative community Be surrounded by extraordinary ideas - and the people who discover them About Us The Department of
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, they will have prior knowledge of infectious disease modelling, Bayesian inference methods and optimisation methods. They will have a developing research profile, with a demonstrated ability to publish
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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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), 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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. Proficiency in deploying and managing wildlife camera‑trap networks and processing large image datasets. Experience developing and validating machine‑learning and AI models for image object detection and
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. Demonstrated ability to communicate and interact with a diverse range of stakeholders and students. An understanding of and commitment to UNSW’s aims, objectives and values in action, together with relevant
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superannuation) Amplify your impact at a world top 50 University Join our inclusive, collaborative community Be surrounded by extraordinary ideas - and the people who discover them The Opportunity The Department
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judgement and initiative. Excellent written and verbal communication skills, with a high level of attention to detail. An understanding of and commitment to UNSW’s aims, objectives and values in action
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internationally. Key responsibilities include: Developing and standardising methods to detect and analyse microplastics in soils and livestock. Establishing an Australian data inventory on microplastic
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collaborative networks both nationally and internationally. Key responsibilities include: Developing and standardising methods to detect and analyse microplastics in soils and livestock. Establishing