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edge techniques including confocal, total internal reflection microscopy, AFM, QCM, cryo-TEM and x-ray scattering. This is an ARC-RMIT co-funded scholarship providing a stipend of $33,826 per annum (pro
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In the PhD program, you will be involved in working with a multi-disciplinary team. You will be conducting experiments and developing phenomenological models to understand the graphite formation
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This project expects to generate new knowledge in the area of circular economy by using place-based and practice-led approaches to foreground the experiences, artefacts, processes and communities
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. There is a high likelihood of continued employment with a competitive numeration at APV Engineering, after the completion of PhD. This is a co-funded highly competitive scholarship, only available
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achievement of 70% or higher and a High Distinction is 80% or higher. The minimum requirements for admission to a Doctor of Philosophy (PhD) program are: a bachelor's degree requiring at least four (4) years
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Are you an Australian PR, citizen, or an international student in Australia with a 1st class Honours in Chem/Mech Engineering, Physics, or Maths? RMIT Engineering PhD candidates get a laptop, world
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) 2 (two) Standard RMIT PhD enrolment requirements apply. Candidates should have an undergarduate degree in a relevant field of science or engineering. Standard RMIT PhD enrolment requirements apply
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The scholarship provides a minimum stipend of $34,481 each year for three years to perform experimental investigations and developing mathematical models to valorize waste and produce carbon nano materials. The scholarship provides a minimum stipend of $34,481 each year for three years to...
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Sustainable management of organic wastes is critical for greenhouse gas emissions reduction and circular resource recovery. Organics management via biological and thermal treatment can offer
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@rmit.edu.au Dr. Shao, Wei (Data61, Marsfield) - wei.shao@data61.csiro.au The successful candidate is expected to have strong motivation and evidenced skills in machine learning and computer vision