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PhD Scholarship Opportunity - Processing intelligence for green metals using in situ X-ray characterisation and machine learning Job No.: 693787 Location: Clayton campus Employment Type: Full-time
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applied mathematical modelling machine learning multi-fidelity modelling numerical methods. Demonstrated programming ability (MATLAB/Python/C++) and enthusiasm to learn PyTorch. Previous experience in one
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Applications are open The PhD project is part of a collaborative project: ‘A “virtual market” for analysing the uptake of energy efficiency measures in residential and commercial sectors’, funded by
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language processing, large language models, machine learning, network analysis, social media analytics, and large-scale analysis of online discourse and communities. This PhD scholarship will be based within
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. • be located at the agreed project location(s) and, if required, comply with the university’s external enrolment procedures. Selection criteria Skillset: Proficient in Python, machine learning, and
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languages, including Python, C++, or Java, focusing on algorithms and data structures applied explicitly in computer vision projects Knowledge of machine learning and deep learning frameworks, including
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national PhD scholarship. Additional support is available for project resources and conference attendance. Be inspired, every day Drive your own learning at one of the world’s top 80 universities Take your
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systems, intelligent sensing, advanced materials, and nanoscale device technologies. The successful candidate will develop machine learning approaches (including generative models and physics-informed
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the perceived enablers and constraints within different organisational and cultural settings. Second, drawing on these findings, the project will work collaboratively with coaches, sporting
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: opportunities to utilise prototype automated vehicles, new test tracks, and advanced digital twin infrastructure. Industry integration: direct collaboration with industry leaders and government stakeholders