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model with each SNP independently, perhaps adjusting for other covariates such as age and sex. This project will focus on developing and applying novel machine learning and AI methods to improve
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Candidates should hold a previous degree (Bachelor’s and/or Master’s) in Computer Science, Data Science, Robotics, Mechatronics, or Software Engineering, with demonstrated knowledge in machine
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Computational simulations are now widely employed to study the behaviour of social systems, examples being market behaviours, and social media population behaviours. These methods rely heavily
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Automated Program Repair (APR) is the grand challenge in software engineering research. Many APR methods have shown promising results in fixing bugs with minimal, or even no human intervention
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to Fisher-Rao geometry and develop theoretical results characterising MML estimation under various regularity conditions. Aim 2: Development of Computational Methods for MML Design and implement efficient
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, in various formats including images, texts and numeric values. The study of these unstructured data in the pathology laboratory information system (LIS), together with the information from
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This project draws on a recent Dagstuhl Seminar (https://www.dagstuhl.de/en/program/calendar/semhp/?semnr=18322) that brought together leading experts from industry and academia, including those who
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(or equivalent) in a health-related field Experience with mixed methods research, systematic reviews & data analysis Strong communication and organisational skills Australian citizenship or permanent
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become overwhelmed, slower to respond, and more likely to overlook genuine indicators of compromise. A range of methods have been explored to reduce false alerts, including provenance-based analysis and
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relevant field or equivalent experience Strong administrative, numerical and computing skills Experience with systems like SAP and Callista Exceptional organisational and communication skills A proactive