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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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tasks undertaken by this role include assisting the Treasurer with completing bank documentation, general financial markets dealing activities, providing cashflow inputs for the annual budget process and
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empowered by Artificial Intelligence of Things (AIoT). By digitally representing physical objects and harnessing real-time IoT data, our goal is to enhance productivity and reduce maintenance costs for our
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excited by identifying and managing gaps in P&C services including reporting, policy simplification, and process training and improvements. We want to position VU as an employer of choice and your
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digital and physical library service experiences. Conduct user and UX research to embed human-centred insights into library work and decision-making. Oversee library experience and product design, applying
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client service perspective to process improvement initiatives. About you You will be a motivated and experienced administrative professional with a passion for delivering and promoting exceptional client
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requirements, and assist with the design of solutions which effectively deliver desired outcomes. Perform a lead role in driving process improvements, investigating, analysing, and documenting business processes
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to support you prepare your application is available on our website. If you experience difficulties applying online or need reasonable adjustments at any point in the application or interview process, please
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the complex interactions of gangue minerals during the reduction process, focusing on the formation of fayalites and low melting point aluminosilicates, which can affect metallisation and the reduction kinetics
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University of Western Sydney | The University Of Sydney, New South Wales | Australia | about 4 hours ago
! 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