124 postdoctoral-image-processing-in-computer-science-"Multiple" PhD positions at RMIT University in Australia
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applications. This project would suit people from a wide variety of backgrounds, including food technologists, chemistry, food scientists, and chemical and process engineers. In this project you will gain skills
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investigations at macro, micro and molecular levels. Modeling tools such as HSC Chemistry and ASPEN Plus will be used to identify most suitable low cost catalysts/minerals and to perform process modeling
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project will adopt a mixed-method design with interviews and quantitative surveys conducted with multiple stakeholders including Vietnamese businesses and citizens, academics and practitioners. Therefore
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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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This project aims to develop and apply quantum microscope techniques to image magnetism in 2D materials. Initially, the student will be involved in the experimental realisation of these quantum
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models Working closely with industry partners through internship program RMIT School of Engineering Scholarship is available for an aspiring chemical engineering graduate (BTech/Masters) to conduct
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Research degree; or a Master by Coursework degree with a significant research component graded as high distinction or equivalent; or an Honours degree achieving first class honours in Computer Science
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Scholarships are open to domestic or international students. The successful applicant must have already applied for, or have already commenced a PhD research program at RMIT and accept Data61 scholarship
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large language models (LLMs). Candidates should have an interest or experience in culturally inclusive AI safety, multilingual NLP, AI ethics, or computational social sciences, and must hold a relevant
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The primary objective is the development of computational methods and experimental techniques to investigate failure modes and quantify defects and damage in fibre reinforced hybrid composites used