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evaluation and quality improvement. The candidate will be supervised by clinician-researchers, A/Prof Alison Salt (Consultant Paediatrician) and Dr Sarah Hall (Clinical Neuropsychologist), and with support
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, biology, engineering, machine learning / data science, coding. How to apply: This is an Expression of Interest process. To express your interest in applying, candidates must supply the following information
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biology: How do epigenetic features contribute to the regulation of the genome? We study how chromatin drives specificity for regulating gene expression. You will be dissecting the molecular features
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manufacturing practices with real-world industry application. This full PhD scholarship is based at Swinburne’s School of Science, Computing and Engineering Technologies in Melbourne. The successful candidate
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impact in translational fields, which often aim to use generative AI in a responsible way. This PhD project is part of a larger cohort of projects in the Monash AI Institute, a recently expanded program
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at laboratory scale using small-area gas-diffusion electrodes (<5 cm²). Scaling up these systems introduces significant engineering challenges, including mass transport limitations, long-term catalyst durability
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project within an NHMRC-funded program focused on dementia research. Using a systems biology framework, the project will integrate genomic and lifestyle data to identify key molecular pathways and risk
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discipline, complete an expression of interest (EOI). The steps are: Complete the EOI available at Next Generation Graduates Program (NGGP): Sports Data Science & AI - Centre for Data Science (qut.edu.au
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Applied mathematics, fluid mechanics, high-performance computer simulations. Full time, fixed term position (3 years) at Hawthorn campus $34,700 per annum (2025 rate) About the Scholarship Higher
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science technologies, and this is a perfect training opportunity for those who is interested in machine learning, data mining, artificial intelligence, and bioinformatics. High-performance computing may