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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
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to three years of study (with the potential for extension) Scholarship Details Maximum number awarded 1 Eligible courses The successful candidate must enrol into a Doctor of Philosophy (PhD) program
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brings together an industry partner, a university and Australia’s leading science agency, CSIRO, to co-develop a four-year industry-focused PhD project. The program supports a three-way partnership aiming
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. You will also receive either: an Australian Government Research Training Program (RTP) fees offset a QUT research degree (HDR) tuition fee scholarship. As the scholarship recipient, you will have the
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PhD Scholarship This project aims to develop novel catalysts and reaction systems for energy-efficient electrochemical conversion of captured CO2 into liquid fuels. Electrochemical Conversion
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/admissions/entry-requirements/minimum . Candidate Requirements Undergraduate honours degree or Master's by research degree in a relevant discipline (Computer Science, Robotics, Engineering or others related
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program, leading to joint PhDs with degrees from both universities. Applications are sought from outstanding candidates with backgrounds in chemistry, physics, materials science and related disciplines
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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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knowledge of health economics, but this is not a requirement as training will be available throughout the PhD program. Stipend: The scholarship will be for 3.5 years and has a stipend of $35,300 (indexed