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clients at all levels. Highly proficient computer literacy with excellent skills in Microsoft Office and clinical software applications. Ability to plan, organise and co-ordinate projects and tasks
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) to support surgeons, operating room technicians, and other professionals in and around operating room activities. Particular areas that may be explored are: Immersive OR analytics: using XR to analyse data
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Registration, and completion of mandatory immunisations. This may also include checks relating to gender-based violence matters or other integrity and conduct requirements. For further information about this
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for more information. The opportunity We have a dynamic and inclusive team within the Biomedical Manufacturing program and are seeking applicants for the role of Validation Engineer for a 6-month term. As a
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Manager to lead the delivery of complex digital infrastructure initiatives across Infrastructure, Cloud, Data Centre and Cyber domains. Reporting to the Senior Manager, Technology Mobilisation within
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to: lead best practice in research operations, ensuring compliance and innovation across methodologies and governance direct support design and implementation of advanced data management systems and digital
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including software engineering, computer systems, cybersecurity, databases and data engineering, ethics and artificial intelligence, statistics, data science, and the Internet of Things. Staff will also be
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University of New South Wales | Canberra, Australian Capital Territory | Australia | about 20 hours ago
, policy reports and analytics. Experience with data and analytics desirable, but not essential. Benefits and Culture: UNSW is committed to helping staff balance work-life responsibilities, by providing
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allow you to select your area of interest, which courses you would be interested in teaching as well as providing information on your qualifications and experience to assess your suitability for any roles
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Minimum Message Length (MML) is an elegant information-theoretic framework for statistical inference and model selection developed by Chris Wallace and colleagues. The fundamental insight of MML is