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the observer. Active Goal Recognition extends Goal Recognition by also assigning the data collection task to the observer. This Ph.D. project will provide a unified probabilistic and decision-theoretic
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and maintenance of information systems and digital services using a wide variety of tools and platforms, including but not limited to web, mobile, conversational AI and cloud infrastructure. This is a
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improvement of the system, coordination with the users and other key stakeholders (internal and external) to ensure data accuracy and system integrity, and ensuring the system meets the University’s strategic
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Time series are an ever growing form of data, generated by numerous types of sensors and automated processes. However, machine learning and deep learning methods for analysing time series are much
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combination of multi-wavelength observational data with sophisticated simulations. I am a member of various collaborations, including Australia's OzGrav Centre of Excellence for Gravitational-wave Discovery
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months, and link survey data to national administrative data systems for longer-term follow-up. The successful candidate will play a leading role in all aspects of the cohort study, including its design
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, and drive continuous improvement. Deliver high-quality customer service through timely issue resolution and effective stakeholder engagement. Contribute to data analysis, reporting, governance
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excellence. Knowledge of student placement processes, data management and privacy and compliance requirements is essential alongside experience using student information systems and placement databases such as
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threatened species and ecosystems, and to control invasive species and diseases. This requires a step-change in the data and methods used to monitor and predict organism behaviours and ultimately shifts in
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information about behavioural patterns, but scoring this manually is time consuming. For this reason, machine learning solutions have been developed to automate behavioural prediction [5-12]. DeepLabCut [5] is