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gendertransformative health promotion in rural and remote Queensland. Research focus The research question and project design will be shaped by you, the candidate, and your interests and experiences. Potential areas
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digital health and multi-agentic coordination. This role requires the development of self-learning artificial intelligence models tailored for dynamic healthcare environments. The candidate designs and
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physics-based and data-driven methods to support the design and scale-up of these systems. This approach will reduce the need for costly experiments, improve scale-up predictions, and provide confidence
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, community leadership, and evidence-informed practice. Project details The research intern will work within the Research and Innovation Directorate and contribute to projects aligned with KWY’s strategic
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range of Professional Doctorates, including the Doctorate in Heritage, Doctorate in Design, and Doctorate in Fine Art. One studentship each year (either full-time or part-time) will be allocated for a PhD
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, the successful candidate will be expected to: Develop a conceptual modelling and digital twin framework for smart remanufacturing systems to enhance decision-making under uncertainty. Design and implement
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loaded in a lab setup. High resolution cameras will be installed to capture the elastic and thermal changes in the material during the loads. Distinct experimental scheme will be designed initially
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for e-DAC. The research will involve molecular-level modeling and data-driven analysis to guide the design of redox-active capture materials, combined with experimental validation in electrochemical cells
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to implement adaptive manufacturing strategies that respond dynamically to process variations. The “design-manufacture-inspect-model-test” approach of this project will equip the successful PhD candidate with a
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regular input from Laminar , the industrial sponsor of this project. You will be taught a range of skills to complement, drive and strengthen your research: design of experiments, life-cycle analysis