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optimisation.” The successful candidate will be involved in developing new mathematical theory and designing and implementing optimisation algorithms relevant to quantum information. The Research Fellow will
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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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and innovation catalyst, in this exciting project, you will develop novel algorithms to monitor and analyse workers' movements, detect harmful movement patterns, and implement simple intervention
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learning approaches to enable multi-site collaboration while preserving patient privacy. This ensures more generalized and reliable reconstruction models that can adapt to diverse data distributions
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PhD student(s) will join a vibrant team of postdocs, academics, and up to four PhD students working collaboratively across modelling, qualitative fieldwork, and optimisation techniques. PhD Research
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distribution across multiple HSR scenarios. You will work alongside a team of internationally renowned experts in transport and urban planning, including Associate Professor Liton Kamruzzaman, Professor Hai Vu
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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, including Coolant Distribution Units (CDUs), and water-cooled server racks in data center environments. Solid understanding of data centre physical infrastructure best practices, including airflow management
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-tracking, pupillometry), cognitive modelling, and regulatory analysis to assess how algorithmic explanations shape human judgement and how existing legal and ethical frameworks align with the evolution
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the headspace website. Possible approaches to addressing this challenge might include: Developing algorithms to identify patterns and preferences based on service users’ previous content engagement