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new x-ray imaging techniques from the synchrotron to the laboratory Transforming breast cancer imaging with x-ray phase contrast Webpage: https://xrayimagingmonash.wordpress.com/ For further details
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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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they fulfil the criteria for Masters by Research & PhD admission at Monash University. Details of the relevant requirements are available at https://www.monash.edu/engineering/future-students/graduate-research
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here: https://www.flinders.edu.au/study/apply/apply-research-degree/how-to-apply By lodging this separate application, applicants acknowledge: The ‘Supervisor confirmation’ must refer to the application
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. Qualifications Mandatory: Mandatory: PhD or equivalent in relevant field. Please Note: Appointment to this position is subject to passing a Working with Children and National Police Check. To Apply Please submit
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support package over a period of up to 3.5 years for full-time studies and 7 years for part-time studies. It is intended that the Activity Lead undertakes a PhD full-time. An exception to this may be
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group of PhD researchers who will tackle the most pressing questions in Machine Learning while ensuring AI serves humanity responsibly. You'll work within one of our specialised research themes, each
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Status: Open Applications open: 7/01/2022 Applications accepted at any time View printable version [.pdf] About this scholarship Description/Applicant information Two PhD student scholarships
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PhD in Computer Science, AI, Machine Learning or related field Experience Strong track record of publications in top-tier venues (e.g. CORE A*) Expertise in reinforcement learning, AI agents, and LLM