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different care settings – general practice clinics, pharmacies, nursing homes, patient homes (face to face, telephone, video conference), conducting point of care testing, biometric measurements, and
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is like Ockham's razor, seeking a simple theory that fits the data well. It can also be thought of as file compression - where data has structure, it is more likely to compress, and the greater
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opportunity to work across a wide variety of projects, including events, communications projects including social media, news stories, video scripts, presentations, reports, web content and more. You will have
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with real-world application to pressing health challenges. In this role, you will: Develop new statistical methodology to support adaptive variants of cluster randomised trials Write R or Stata code
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Be selected and fulfil the requirements of an Access Monash Mentor . Written application and performance at a video interview. To retain this scholarship: Fulfil the requirements of an Access Monash
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, and data protection Apply engineering principles, including version control (e.g., Git), CI/CD pipelines, and infrastructure-as-code (IaC) to ensure robust and repeatable deployments across both
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question and answer tool for Crank crew members to prepare for coaching sessions around specific video gaming topics. Moreover, the PhD student will complete natural language processing and machine learning
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of research and teaching activities involving animals to ensure the use of animals is justified and has scientific merit and animal welfare is prioritised, in accordance with the Australian Code for the care
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Code for the care and use of animals for scientific purposes (8th edition 2013 (updated 2021) (the Code)). The AEC is comprised of members across various categories as stipulated in the Code and includes
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statistical analysis and/or coding (e.g., R, Python, C++) Exposure to neurophysiological measurement methods (e.g., eye-tracking, pupillometry) Interest or training in technology law, digital regulation, or AI