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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
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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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, machine learning, and image processing techniques Strong candidates with electrical, mechanical, and biomedical engineering backgrounds can also apply. To be eligible for this scholarship, you must: Meet
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charge which provide an ideal interface between human-built devices (where signals are carried by electrons) and biological systems (where signals are carried by ions). This research will cover theoretical
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applicant will receive a tax-free stipend, at the current value of $36,063 per annum 2025 full-time rate, as per the Monash Research Training Program (RTP) Stipend www.monash.edu/study/fees-scholarships
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, resulting in faster and more cost-efficient signal modelling. However, embedding physical constraints within the network architecture remains a significant challenge. Current research often integrates
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-based molecular biophysics project of medical significance, funded by the National Institutes of Health, USA. The Computational Biophysics Group develops advanced physical and chemical simulation
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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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PhD Scholarship in Digital Mapping of Homemade & DIY Cultural Economies in First Nations Communities
appointment Remuneration: The successful applicant will receive a Research Living Allowance, at current value of $52,352 AUD per annum 2025 full-time rate (tax-free stipend), indexed plus allowances as per RTP
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description of how these proteins respond to physiological stimuli to control electrical signalling the body. This project, in collaboration with researchers at Cornell University, USA, is funded by