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health economics, labour economics, economics and econometrics. We will also consider other quantitative disciplines such as data science, mathematical statistics, actuarial science or public health
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from other quantitative disciplines – such as data science, mathematical statistics, actuarial science, public health, or psychology – who have strong quantitative skills and an interest in causal
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, and industry audiences. Reproducible outputs including: Analysis protocol Validated questionnaire scoring framework Aggregated datasets (de-identified/synthetic) Statistical analysis code
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from other quantitative disciplines – such as data science, mathematical statistics, actuarial science, public health, or psychology – who have strong quantitative skills and an interest in causal
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mathematical concepts such as optimization, linear algebra, probability, and statistics, relevant to AI and quantitative modelling. Technical proficiency in programming66: Demonstrated programming skills with
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Statistics for the Australian Grains Industry 3 (SAGI3). Investment. The University of Adelaide, in collaboration with Curtin University and The University of Queensland, is leveraging machine learning, data
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candidate. The PhD project will focus on data analytics, data mining, and statistical modelling of complex biological system in crops. The project will have access to large volume of state-of-the-art Next
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Desirable skills Experience with experimental design and behavioural data collection Familiarity with generative or agentic AI systems, explainability (XAI), or algorithmic fairness Skills in statistical
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statistical competence in quantitative methods. They will have a demonstrated ability to work independently and to appropriately manage sensitive and confidential information. Responsibilities may include
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models that can forecast the likely outcomes of current practices. The project aims to develop cutting-edge machine learning and statistical risk prediction techniques to predict each short-term, long-term