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Research Fellow to engage in research on the area of data analytics, modelling, machine learning and process control to further their expertise and growing research profile in their discipline. The focus
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Exciting postdoctoral role for an early career researcher with a PhD in GHG modelling, process-based modelling, model integration, environmental engineering, ecology, agricultural modelling. Play
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knowledge and skills in health system and process mapping. The project is being undertaken in collaboration with the Integrated Sustainability Analysis team in the School of Physics and the Central Clinical
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for material flow analysis and hybridising physical, financial and economic data in the context of carbon footprinting techniques and will be working as part of a larger multidisciplinary team. The project is
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must: hold (or be about to complete) a PhD in physics, physical chemistry or a closely related discipline; provided the applicant has a relevant research background. have a research background in
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! The Postdoctoral Research Fellow will work on an ARC Discovery Grant (DP220100795) aimed at the development of physics-aware machine learning models for spatially explicit fire risk forecasting in Southeast
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stability, and accounting for the physical protection that comes from soil aggregates. The CERC Fellow will lead the development of next-generation analytical pipelines to measure biologically significant
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submitted via the application link provided – applications via direct email will not be considered due to Curtin Equity policies. Essential Criteria: A doctorate in a relevant discipline area such as physics
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to the mineral processing industry across a range of areas, including comminution, process modelling, experimental test work, equipment selection and operation. Excellent technical skills and experience in
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Part time (0.2 FTE) fixed term contract up to 3 years Be a part of The School of Health Sciences, which is ranked number four in the world for sports, physical therapy, and rehabilitation Base