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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 months ago
at ANU. We are a transformative centre for research in artificial intelligence and machine learning, computer systems and software, and theoretical foundations of computing. We span traditional and modern
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DEMANDS: Frequent, prolonged sitting, moderate standing, moderate walking, bending, travel to various sites/locations. Extensive reading required. Extensive computer work required. Periodic speaking
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development of computer systems for data analysis, development of machine learning methods, and the clinical use of technology. Within the research groups you will therefore work together with computer
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The fellow will be responsible for: Building collaborations with our multidisciplinary team (medical physicists, engineers, computer scientists, nuclear medicine physicians) to develop and implement innovative
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skills relevant to maintenance, repair, and modification of scientific instruments. Qualifications Experience with biological experimental design and implementation. Computer skills for instrument
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scientists, nuclear medicine physicians) to develop and implement innovative AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical
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epilepticus. You will work in the group of academic neurologist and computer scientist Dr Gregory Scott, with a team of collaborators having expertise in translational neuroscience, clinical neurology, signal
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sensing systems, including recent NOAA and NASA satellite launches, and computer modeling systems. Mentor: The mentors for this opportunity are Susan O’Neill (susan.oneill1@usda.gov ), Sim Larkin
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About Cookies Cookies and related technologies (herein “Cookies”) are small text files that a website saves on your computer when you visit the site. Cookies the University sets are called first
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have exceptional resources to facilitate research including access to administrative, research, and computer support staff. Required Qualifications* PhD degree or equivalent in epidemiology, gerontology