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including hybrid on site/WFH options and flexible start/finish times, and genuine career progression opportunities via the academic promotions process. About You Completion of a PhD in the fields of geography
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-making processes in relation to environmental, biodiversity and climate policies. This project will provide the first comparative empirical data on, and analysis of democratic reforms that expand
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the academic promotions process. About You Education, training and/or relevant experience equivalent to the completion of a PhD in a relevant field (e.g., natural products chemistry). Strong expertise in organic
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discipline, including publications in high-quality peer-reviewed journals and presentations at major conferences. Demonstrated high-level mathematical and computer programming skills. Where PhD has been
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
here . For enquiries about the application process, or if you require reasonable adjustment to apply for this role, please contact the hiring manager on the above listed details. Application information
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to people of all backgrounds and identities. For more information about staff equity at ANU, click here . For enquiries about the application process, or if you require reasonable adjustment to apply
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and uphold university values. This is a research focused position. Further information can be found by viewing UQ’s Criteria for Academic Performance . About You Completion or near completion of a PhD
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Proficiency in analytics, AI, and modern data science tools Excellent problem-solving, project coordination and communication skills A PhD or equivalent research experience (preferred) Experience with clinical
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including hybrid on site/WFH options and flexible start/finish times, and genuine career progression opportunities via the academic promotions process. About You Completion or near completion of a PhD in
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data (e.g. DFT, MP2) and experimental data into AI-driven pipelines for structure–property learning and reactivity prediction. Applying AI models to real-world problems in virtual screening, ligand