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their best work. THIS ROLE IS LOCATED IN SYDNEY, AUSTRALIA. The School of Mathematics and Statistics currently has more than ninety continuing academic staff and several dozen research staff as
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 days ago
: The Position Up to two academic positions are available for the project “Analytics for the Australian Grains Industry” (AAGI) within the Research School of Finance, Actuarial Studies and Statistics at the ANU
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their best work. THIS ROLE IS LOCATED IN SYDNEY, AUSTRALIA. The School of Mathematics and Statistics currently has more than ninety continuing academic staff and more than thirty research staff as
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 13 hours ago
of Finance, Actuarial Studies and Statistics at the ANU College of Business and Economics. The successful candidate will undertake a collaboratively designed research program in statistical design and
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 days ago
School of Finance, Actuarial Studies and Statistics at the ANU College of Business and Economics. The successful candidate will undertake a collaboratively designed research program in statistical design
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statistical modelling, to contribute to an ARC-funded Discovery Project investigating the psychology of how people manage competing demands inside and outside of work. The project develops and tests a novel
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aptitude, and proficiency in data handling, basic statistical analysis, and scientific writing. Strong leadership, organisational, and problem‑solving skills are essential, along with the ability to work
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, economics, sociology or a related social science, plus strong quantitative capability, you’ll have the opportunity to apply advanced statistical and econometric methods, publish impactful research, and
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to protocol development, power/sample size considerations, and statistical analysis plans develop and apply advanced modelling approaches (e.g., survival and competing-risk models, causal inference methods
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statistical methods including multilevel modelling, psychometric scale validation (EFA/CFA), structural equation modelling and causal inference approaches appropriate for complex education datasets. Advise