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Completion or near completion of a PhD in Engineering (mechanical, aerospace, civil, petroleum) or Science (applied physics, applied mathematics) with a strong background in CFD and the finite element method
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imposed timelines/milestones. PhD (or near completion) in Engineering or Applied Science with strong expertise in CFD. Proficiency with open-source engineering software and numerical methods such as FEM
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have a PhD in Computer Science (or be able to demonstrate equivalent research experience in modelling and simulation, software engineering research) and possess a deep and demonstrable knowledge
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and synthesis of new materials. You should have a PhD in a relevant field (Computer Science, Mathematics are most likely to fit the role, but we are open to Chemistry, Materials Science, Chemical
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provided throughout the recruitment process. To be successful you will need Postgraduate qualification relevant to research (Level A); PhD preferred (Level B) Experience implementing data collection and
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, you’ll have: Associate Research Fellow: Master’s degree in Biostatistics or Statistics; alternatively, a PhD in Epidemiology with strong quantitative component. Research Fellow: A PhD in Biostatistics or
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we are looking for (Selection Criteria): Essential: A PhD (or near completion) in geochemistry, geology, data science or a related discipline. Demonstrated knowledge of, or strong interest in critical
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University of Melbourne, The Kids Institute, and associated research higher degree student(s). The appointee will have completed a PhD in applied mathematics, computer science, or a related discipline. Ideally
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presentations. Contribute to grant applications for competitive funding opportunities. Who we are looking for (Selection Criteria): Essential: PhD (or near completion) in Geophysics or a related field or an
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-renewable-energy-engineering Skills & Experience: A PhD in Computer Science or a related field. Thorough theoretical background in machine learning and deep learning. Demonstrated experience in developing