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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 days ago
, including of heavy industry in Australia, working collaboratively with other researchers. Methods are broadly in the field of social sciences, including economics, market modelling and public policy analysis
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to attracting, retaining, and promoting diverse talent. If you require an alternative method to submit your application due to accessibility needs or personal circumstances, please contact talent@uq.edu.au
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scripting for simulation and data analysis, along with experience using high-performance computing environments, is required, and experience using structure prediction and/or machine learning methods is
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diverse talent. If you require an alternative method to submit your application due to accessibility needs or personal circumstances, please contact talent@uq.edu.au . Applications close 31 July 2025
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, mathematical psychology (computational modelling) and/or human factors methods and related statistical techniques (including Bayesian hierarchical methods) Experience with the development and application
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, mathematical psychology (computational modelling) and/or human factors methods and related statistical techniques (including Bayesian hierarchical methods) Experience with the development and application
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collection methods. You’re skilled in developing computational models and deep neural networks that reflect principles of human cognition and brain function. Your academic record includes high-quality peer
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equivalent experience. A passion for research that makes a difference and influencing public policy discourse. Demonstrated expertise in data analytics and econometrics methods and their application to real
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an environment that mirrors our wider community. We're committed to attracting, retaining, and promoting diverse talent. If you require an alternative method to submit your application due to accessibility needs
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extraordinary ideas - and the people who discover them The Opportunity We are seeking a highly motivated Research Fellow to join the Faculty of Science and School of Physics and Astronomy to develop methods