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information about this position and to apply. Senior Program Coordinator (686421) This will coordinate activity across the three large Laureate programs of research in, and manage the implementation of a
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the information encoded in our genome to better diagnose, treat, predict and prevent disease. From the individual patient with rare disease, to the many thousands affected by complex, widespread illness, we
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opportunities for experienced users. About you Previous experience working with large data sources and complex data in the higher education sector. Extensive experience in Adobe Analytics, including tagging and
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for Big Data Research in Health (CBDRH), strategically partnered with the School of Clinical Medicine (Women’s Health) at the University of New South Wales, Sydney (UNSW). This positioning places the NPESU
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Apply now Job no:536446 Work type:Full Time Location:Sydney, NSW Categories:Information Technology, Analyst, Healthcare Data Scientist Employment Type: Full - time (35 hours a week) Duration: 18
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large organisation with a diverse and talented community; a community doing extraordinary things. Together, we are driven to be thoughtful, practical, and purposeful in all we do. Taking this combined
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to cloud-based machine learning services, on-device ML is privacy-friendly, of low latency, and can work offline. User data will remain at the mobile device for ML inference. Problems: In order to enable
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to academic, professional, and external stakeholders, handling sensitive information with confidentiality. Provide general administrative assistance to support teaching and learning tasks, academic onboarding
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 4 days ago
achieving this the Facilities Officer will work as part of a large team focusing on the quality-of-service delivery. For more information about the position, please contact Sophie Taylor, Project Officer, E
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, filter handling, mineralogical or particulate sample processing). Strong data-management skills, including experience with large analytical or imaging datasets, file organisation, naming conventions, and