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We are seeking a Senior Research Fellow (Clinical) to lead research that supports the co-design, implementation, and evaluation of innovative, multidisciplinary team (MDT)-based primary care models
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engagement methodologies for the design of large language model (LLM) agents within digital health interventions. Stakeholders in this context include subject matter experts—such as clinicians, healthcare
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health lens to addressing hearing loss in adults. This program aims to reshape how hearing care is viewed and delivered—shifting from a specialist-driven, clinic-based model to a more accessible
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frameworks, such as PyTorch (preferred) or TensorFlow, with a preference for experience implementing SOTA models and training procedures from academic journal papers. Development of data engineering pipelines
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tools to tackle some of the most complex questions in brain science. As a Level A research-only academic, you will contribute to projects that integrate computational models with experimental neuroimaging
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infrastructure, enabling sophisticated geospatial, isotopic, geochemical and temporal analyses of critical mineral systems. Develop and implement data models following FAIR data management guidelines and tools
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collection methods. You’re skilled in developing computational models and deep neural networks that reflect principles of human cognition and brain function. Your academic record includes high-quality peer
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gyms. Numerous opportunities for professional development including leadership programs and workshops, and our study assistance scheme. Commitment to our Indigenous Australian staff through initiatives
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origami synthesis and characterisation. Previous experience with non-academic and industry projects is desirable. Demonstrated expertise in supramolecular chemistry, computational modelling, and/or
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collaborating with industry partners on a project aimed at developing kinetic Monte Carlo simulations to model epitaxial growth processes. The goal is to control and optimise the growth of nanoscale structures