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PhD Scholarship in ‘Using nanoparticles to enhance the immune response and improve vaccine efficacy’
sorting, multiplex cytokine analysis (Luminex), IVIS imaging, as well as ELISA, ELISPOT, immunohistology/immunofluorescence, proliferation and functional T cell assays. There is also potential scope to use
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Using cancer and vaccine clinical trials, the project will use RNAseq, epigenetics and flowcytometry, as well as classic immunological techniques. Using cancer and vaccine clinical trials
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health, aged care, information technology or public health. They should have a strong interest in digital health, aged care innovation, and technology-driven healthcare solutions. Candidates must possess
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and industries across all areas. PhD candidates under this program are connected with academic supervisors and industry-based researchers, to co-design innovative, applied research projects. Through
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(Level A) $78,544 to $105,611 per annum plus an employer contribution of 17% superannuation applies. Fixed-term, part-time position (0.6 FTE) available for 2 years. Grant Funded Early Career
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. To apply, please submit the following documents to Prof. Magdalena Plebanski (magdalena.plebanski@rmit.edu.au ) and Dr Kirsty Wilson (kirsty.wilson2@rmit.edu.au ). A copy of electronic academic transcripts A
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the following skills and qualifications (tailored to the specific project): Driven individuals who want to be a part of a world class team Some familiarity in healthcare or engineering/image based analysis
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evidence underlying C2 Agility is based mainly on descriptive studies that use cross-sectional or low-resolution (i.e., broad timescale) snapshots of key inputs, processes, and outputs obtained within static
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-style interventions, and preventative medication. Analysis will utilise best practice in health inequalities measurement, modern econometric techniques, behavioural experiments, and modelling
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relevance across various surgical procedures and patient groups. Objectives 1. Algorithm Development: (a) Design and implement a deep learning algorithm for CT scan analysis. (b) Train, validate, and test the