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must support causal queries about what would happen under intervention, generalise reliably to deployment contexts not present in training data, and expose its reasoning chain to inspection so that risk
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Research data governance is an under-explored issue, and technical infrastructures to support the transparency and control of data collected in human research studies (from medicine to social
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someone with strong quantitative skills and an interest in using data to answer policy relevant research questions. The successful applicant will work with large administrative and survey datasets and apply
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. Demonstrated success in generating research income and managing large research projects/teams. A commitment to team science, open, responsible research (FAIR data), and a collaborative mindset. About Monash
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financial reporting within a complex, asset-intensive environment (specifically asset and leasing accounting). Knowledge and Skills: Proven experience working with SAP (or equivalent large financial system
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As education systems increasingly adopt AI to support teaching and learning, the automation of assessment and feedback processes has emerged as a critical area of innovation. Large-scale learning
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, and costs of running diverse applications in large-scale distributed systems. This project offers researchers and students a chance to explore cutting-edge concepts in AI-driven infrastructure
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investigate how large language models, recommender systems, advertising systems, and data brokers may infer sensitive traits such as personality, emotional state, political inclination, social vulnerability
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. Analysis of this data will employ both qualitative and quantitative methods. Work on WP-2 will suit someone with an interest and aptitude for coding administrative data using large language models. It will
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market insights, data and emerging trends to identify opportunities and inform decision making. Build strong partnerships across the University and with external stakeholders to maximise impact and