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computational tools for quantifying electromagnetic field distributions down to the fundamental atomic scale. The project will build on recent developments in inverse scattering methods, including ptychography
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peer-reviewed publications, while providing senior-level expertise to support and mentor internal teams. A vital responsibility includes guiding emerging science-practitioners (Clinical Psychology PhD
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such models and produce reports and scientific papers on this work. The successful candidate will have a PhD qualification in AI, computer science, atmospheric science, climate science. You will also
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(Level A or Level B) to join our team on the ARC Linkage Project: “Building Australia’s Electric Vehicle Fast Charging Infrastructure.” This collaborative project brings together leading researchers from
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attract international scholars, PhD students, and Research Fellows, contributing to innovative research that shapes the field. Ranked among the top 10 institutions in Econometrics, Time Series, and
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will conduct independent and collaborative research, publish in high-impact journals, and present findings at major international conferences and workshops. You will also mentor and support PhD and
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that unveil the unseen. analyse complex data to uncover insights and pioneer new strategies for molecular sensing and imaging. We’re looking for someone who brings: A PhD in chemical biology, organic chemistry
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closely with academic staff and provide guidance and support to junior researchers and students involved in the project. Ideally you will have a PhD in Economics of Education or expect to receive it by
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, neuroimaging, genetics, and comparative neuroscience. This role offers a platform to build your research profile, collaborate across disciplines, co-supervise students, and contribute to high-impact discoveries
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focused on optimisation technology and its application in architectural design. About the Role: You will work on a dynamic project aimed at developing automated optimisation approaches to enhance building