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continuous improvement in business operations, finance, governance, and resource management. Support research excellence by coordinating key activities such as workshops, translation initiatives, and large
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 days ago
develop teaching and science communication skills. The Person We are looking for a qualified computer scientist or computational linguist with demonstrated expertise in training large language models and
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– Core Applications This role provides strategic custodianship of the University’s core student information systems, including SiMS (PeopleSoft Campus Solutions) and integrated applications. It ensures
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Victoria and consistently ranked in the top 1% of the world's universities. As a Digital Content Producer, you will: Plan and manage large-scale content projects, collaborating with stakeholders to deliver
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continuous improvement in business operations, finance, governance, and resource management. Support research excellence by coordinating key activities such as workshops, translation initiatives, and large
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 days ago
psychometric equivalence across languages and contexts. Collaborate with computer science colleagues to develop novel personality instruments for unstructured text data. Position Overview This post-doc
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will have a strong track record in research leadership and large-scale infrastructure management, with the ability to guide investment, strategic planning, and operations across complex facilities
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, management, analysis and publication of large-scale longitudinal cohort and qualitative data. Prepare grant and funding applications, research reports and academic publications that advance understanding and
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. Respond to researcher queries regarding data availability and analysis. About you Relevant tertiary qualification or demonstrated equivalent competency. Experience working with large datasets, programming
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, economic growth, inequality, and culture. The project draws on large-scale data collection and archival records, and applies a diverse set of methodologies such as text analysis and machine learning