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Field
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automation methodologies and software infrastructure for next-generation computing systems, including neuromorphic and emerging hardware platforms. The position involves designing high-performance algorithms
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user groups to incorporate scattering datasets into multimodal AI frameworks combining experimental measurements and simulations. Contribute to the development of automated data processing and analysis
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Sustainable and Functional food: Sustainable food systems & circular food economy - alternative proteins, upcycled ingredients); AI & automation in food manufacturing - smart sensors, digital twins, and AI
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), automated testing, and documentation for open-source research software. Preferred Qualifications: ● Experience with neuroimaging data modalities (e.g., EEG, fMRI) and familiarity with how empirical neural
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robotics, automation, artificial intelligence (AI), and data-driven technologies. This is a multidisciplinary collaborative project supervised by Dr John Ward, Professor. Andy Cooper FRS, and Dr Gabriella
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releases in computational neuroscience. * Familiarity with scientific software development best practices, including version control (Git), automated testing, and documentation for open-source research
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. Ability to analyse data and interpret results will be necessary. Industrial Electronic Engineering and Automation, Computer Science or equivalent degrees will be welcomed. Where to apply Website https
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Australia’s manufacturing sector through intelligent automation, technology innovation, and workforce development. This collaborative project will advance the next generation of wear- and corrosion-resistant
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), automated testing, and documentation for open-source research software. Preferred Qualifications: ● Experience with neuroimaging data modalities (e.g., EEG, fMRI) and familiarity with how empirical neural
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and automation of lab equipment using Labview or similar, TCAD simulation and physics-based modelling and cleanroom device processing. A willingness to work together with, and co-supervise, PhD students