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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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the area of end-to-end modular autonomous driving using computer vison and deep learning methods. This includes developing an efficient and interpretable image processing, vision-based perception and
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Australian Imaging Service platforms. Work will include enabling Kubernetes deployments, developing GitOps solutions, the integration of different storage endpoints using the Container Storage Interfaces
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-powered mineral prospectivity modelling codes. As Postdoctoral Research Associate - EarthBank you will; Your key responsibilities will be to: Spearhead research into the development and utilisation of open
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contribute to the design and implementation of an out-of-lab quantum, magnetometer based on OLEDs. Field test and benchmark a prototype OLED quantum magnetometer. Align with and actively demonstrate the Code
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tools in combustion. Our computational codes are also used by various international research institutions. Both experimental and numerical projects are conducted in parallel providing a platform for
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achieve recognition and impact in the research area, design PCBs and develops FPGA code, develop image signal processing systems and sensor motion control, collaborate on the assembly, alignment, and
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proactive project support and administrative services to the School, including maintenance of digital filing systems, spreadsheets, image databases, websites and other administrative systems. Manage the
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advanced imaging (AFM, TEM), fluorescence spectroscopy, and biostructural tools; and collaborate with a diverse team of students and researchers across chemistry, biology, and materials science
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journals. Prototype electrochemical devices based on research results. Undertake additional research responsibilities within the field of expertise. Actively apply for external grants and fellowships with