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Job no:517174 Work type:Fixed term - Full-time Campus:Adelaide Categories:Level A, Level B (Level A/B) $102,024 to $135,932 per annum plus an employer contribution of 17% superannuation applies. Fixed term, full time position available for 2 years with a possibility of extension. About the...
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Status: Closed Applications open: 1/07/2024 Applications close: 18/08/2024 View printable version [.pdf] About this scholarship Description/Applicant information Project Overview Algorithmic systems
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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The National Industry PhD Program is an Australian Government initiative to enhance workforce mobility among graduate researchers, and to promote knowledge transfer between academia and industries
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for renewable fuel production. Reference notes can be found here . PhD Scholarship details Funding: $37,440 per annum (2025 rate) indexed annually. For a PhD candidate, the living allowance scholarship is for 3.5
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PhD. The duration includes an extension of up to six months (PhD) if approved for your candidature. This is the full-time, tax exempt rate which will index annually. You will also receive an additional
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the youth residential care industry. This fully funded PhD scholarship offers the chance to work alongside leading researchers in residential care, systems thinking, and worker wellbeing at a world-class
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The Mymobility Scholarship is funded by Zimmer Biomet to support a full-time PhD student who is commencing research in orthopaedics and patient monitoring. Mymobility was developed by Zimmer Biomet
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Opportunity to help develop a novel nanophotonic therapy targeting drug-resistant hypertension Full-time, fixed term (3.5 years) position at our Hawthorn campus Annual stipend $40,000 About the Role We are seeking a highly motivated and skilled graduate in chemistry, materials science, chemical...
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models