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The PhD candidate will gain intensive knowledge in innovative processing protocols for complex mineral processing, column leaching, and mining site environmental science through hands-on experiments
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Are you passionate about energy efficiency and developing technology to reduce climate emissions? We are offering a fully funded PhD project with a tax-free stipend of $35,888 per annum for 3 years
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The successful candidate will be located in RMIT’s School of Education alongside another COMBS PhD candidate working on a related, educational pathways project. As a member of the COMBS Centre
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PhD Scholarship in Quantum Diamond Synthesis, supporting a Linkage Project between Quantum Brilliance, RMIT University and La Trobe Universities. The goal of the project is to help develop diamond
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at an Australian university; hold an appropriate visa to study in Australia (if international); be no further than one year (FTE) into a PhD candidature on commencing at CSIRO; hold a primary scholarship; for
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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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, robotics or chemistry Standard RMIT PhD enrolment requirement. Open to Domestic and International Students. All applicants should email the following to Ivan Cole@rmit.edu.au : A cover letter, outlining
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This project will examine the behaviour of nanocarriers at cell/bacteria surfaces and response to biological environments and molecules (such as proteins). Research will utilize a suite of cutting edge techniques including confocal, total internal reflection microscopy, AFM, QCM, cryo-TEM and...
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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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@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