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A student with a strong background in statistics with Honours or Masters, excellent computing skills in R or Python, and an interest in working with biochemists and medical researchers. A student
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information systems) Have a strong background in quantitative research and methods, including handling large datasets Have a sound understanding of statistics and experience using multi-level statistical
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., routing decisions through bushfire-affected communities); conduct experiments with participants to collect data on decision-making during simulated bushfire events; and develop statistical models
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responsible for delivering key insights, information and data products to stakeholders across the university by leveraging techniques such as statistical modelling, machine learning and data visualisation. You
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governance framework of the university. To be successful in this position, you’ll have as a minimum: Demonstrated experience and understanding of basic statistical tests, distributions, and a range of analysis
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finite element analysis (FEA). Data Analysis and Statistics: Knowledge of statistical software packages (e.g., R, Python, SPSS) and data visualisation techniques. Desirable experience Experimental Skills
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science and application of statistics Knowledge and experience in R studio and spatial databases To Apply Please submit your CV and letter addressing the Key Selection Criteria numbers 1-5 and 8 and 11 (from
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operating environment. To be successful in this position, you’ll have as a minimum: Demonstrated advanced capability in statistical analysis approaches and other analysis techniques. Demonstrated experience
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statistical pattern recognition methodologies to generate evidence for practice modification recommendations, enhancing the overall quality of care for animal agriculture and contribute to advancing the science
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Engineer will have a primary focus on the preparation, maintenance and operation of pipelines that deliver datasets, that form the basis of analysis, dashboards, statistical analysis & modelling and data