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Training Program (RTP) Fee-Offset a four-year project expense and development package of $13,000 per annum a three-month industry engagement component with Gelomics a structured professional development and
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overall, with no less than 6.0 in each component How to apply For general instructions on how to apply for roles at Monash, please refer to 'How to apply for Monash Jobs '. To express your interest in
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eligible applicants must: • have completed an Honours Degree with First Class or 2A Honours, or equivalent level, or a Master's degree with a significant research component; • have applied, or currently
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complete their milestone 1 within 6 month of enrolment and remain enrolled on a full time basis for the duration of the scholarship. Enquiries The PhD supervisory team will involve a composition of some of
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of Research Excellence in Paediatric Palliative Care. The PhD program involves the design and conduct of a Discrete Choice Experiment (DCE) to explore how consumers prioritise different elements of paediatric
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questionnaire. Twelve months after dissemination of the material, all households will be sent a follow-up questionnaire. We will randomly select n=20 people (n=10 from each location and stratified by sex), who
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PhD Scholarship in Digital Mapping of Homemade & DIY Cultural Economies in First Nations Communities
, the selection committee will prioritise First Nations applicants who hold an Australian (or equivalent international) Honours or Master’s degree (both in a relevant field), with a significant research component
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engagement component of the scholarship will include an industry placement with Intergrain (Bibra Lake, Western Australia). A suitable candidate can start in January 2025. Student type Current Students Future
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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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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