87 parallel-and-distributed-computing-phd-"Multiple" positions at La Trobe University
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• Multiple casual roles available, commencing early December 2025 • Up to a maximum duration of 5 months • Full time/Part-time (min. 3 days/ .60FTE) • Peak period coverage between December 2025
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PhD Research Scholarship in Substance Use, Public Health and Sociology – Critical moments in responses for children affected by family substance use La Trobe University Job description Amount
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Background Expressions of interest The HERknee CRE PhD Scholarship aims to support outstanding candidates undertaking research aligned with the objectives of the HERknee CRE’s mission to reduce the
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, The University of Melbourne, RMIT University and Deakin University support the operation the program by providing University Coordinators to manage each university’s mentors and placements. The Program Director
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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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Australian or New Zealand citizens or Australian permanent residents. Students undertaking the joint PhD program will be enrolled in a PhD at both institutions. Your supervisory team will comprise of academic
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Australian or New Zealand citizens or Australian permanent residents newly enrolling in a PhD. Students undertaking the joint PhD program will be enrolled in a PhD at both institutions. Your supervisory team
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resources and researchers who work with industry and Government to address the sustainability and liveability issues facing global communities. PhD students in our Joint Doctoral Degree Program will have
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for this position, you will have; Completion, or near completion of a PhD degree or equivalent accreditation and standing recognised by the University or relevant professional field. A strong understanding of
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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