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Artificial Intelligence (AI) is revolutionizing the field of Magnetic Resonance Imaging (MRI) by enabling faster, more accurate, and cost-effective image reconstruction. This project explores cutting-edge AI methodologies, focusing on combining data-driven approaches with physics-informed models...
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home. This has allowed me to dedicate more time to my studies as well as to other things to promote my leadership skills, such as through the Access Monash mentoring program. This opportunity has only
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Ability to work independently and collaboratively within an interdisciplinary team Excellent organisational, communication, and interpersonal skills Advanced computer skills, including Microsoft Office and
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and capabilities as the Graduate Business Services Officers. The Graduate Business Services Program is conducted over an 18-month period with graduates gaining experience through three key areas within
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managed by the Clinical Outcomes data Reporting and Research Program (CORRP), within the School of Public Health and Preventive Medicine (SPHPM) – Australia's largest and most respected School of Public
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Fellowship at LMU Munich, and a postdoc position at RMIT University. My nanophotonics research seeks to uncover the underlying physics in structured light-matter interactions at nanoscale. We aim to develop
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known as Team COMPAS -- includes a number of amazing undergraduate and graduate students, postdocs, alumni, and other fantastic collaborators. Please contact me if you are interested in joining our group
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Department Manager Job No.: 681611 Location: Caulfield campus Employment Type: Full-time Duration: Continuing appointment Remuneration: $120,138 - $132,610 pa HEW 08 plus 17% employer superannuation Amplify your impact at a world top 50 University Join our inclusive, collaborative community Be...
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submit your resume and a short statement addressing why you would make a great Lecturer/Demonstrator in our program. For instructions on how to apply, please refer to 'How to apply for Monash Jobs
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Dowe, 1999a) ensures that - at least in principle, given enough search time - MML can infer any underlying computable model in a data-set. A consequence of this is that we can (e.g.) put latent factor