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Field
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electron microscopy (4D-STEM) techniques. The Research Associate will design and execute in-situ experiments under liquid nitrogen and liquid helium conditions, including developing the hardware and
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. Applying machine learning to New Zealand’s landslide inventories to model landslide location, character and dynamics. Integrating time-series and inventory data to develop new models to predict location
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, dedicated to generating original knowledge and understanding of air and space power issues. FASI places a priority on identifying, developing and cultivating the next generation of air and space thinkers in
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Research Platform (SARRP) and in vivo imaging to develop image-guided radiotherapy (IGRT) strategies for liver and childhood brain cancers. A key focus of this project is hepatocellular carcinoma (HCC
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environmental health. Support fieldwork, co-design and engagement workshops with local stakeholders and community groups Assisting in the development of visualisation tools to support decision-making at the urban
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and diffusion of gases/vapours. This project will investigate and develop methodologies for understanding the key relationships between fundamental materials properties (degree of crystallinity, extent
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third over the past 25 years, which is inferred from sparse soil data and the widespread decline of their avian predators. Recent developments in soil geophones and contact microphones have enabled
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maintenance. However, current technologies are relatively slow and not capable enough to provide quick performance, diagnostic and prognostic predictions for real time applications. With the rapid development
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, at the University of Cambridge, UK. The Postdoc will work together with a team of students and research collaborators on the development of learning-based discovery of robot task/environment designs
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the Clean Energy Processes (CEP) Laboratory . The CEP team conducts research on fundamental aspects of thermodynamics, fluid flow, heat and mass transfer processes with applications to the development