249 phd-studenship-in-computer-vision-and-machine-learning PhD positions in Australia
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-refinement for finite element and scientific deep learning methods (gradient-free adaptation, generalized stochastic gradient descent methods) Salary for PhD students: is AUD32K per annum, tax free
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Status: Closed Applications open: 1/07/2025 Applications close: 18/08/2025 View printable version [.pdf] About this scholarship Description/Applicant information Learn more about Curtin PhD projects
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by an ARC DECRA project. The purpose is to support the PhD candidate to conduct basic research on “Applications of oxide materials for electrochemical water splitting and plastic degradation”. The key
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the application for this scholarship The application for PhD admission will only be assessed where: The applicant is successful in being awarded the scholarship Before applying for the scholarship, prospective
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Institute (NDRI) in the Faculty of Health Sciences at Curtin University invites expressions of interest from suitably qualified candidates for a fully funded PhD scholarship in qualitative research about
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methods for elemental tracking of Ca under biotic and abiotic environments in a range of substrates and microbial metabolic pathways using stable isotopes. A 3 year PhD project available at Curtin
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and Prof Kath Hulse (Swinburne). This PhD project will analyse the role and mechanisms of social communication, learning and social networks in fostering sustainable and energy efficient household
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applications in timing and biology, quantum circuits and quantum computing. Projects will be available at the University of Adelaide, RMIT and the University of Queensland. Eligibility: Applicants must be
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in a full-time program of research consistent with the objectives of Tour de Cure, leading to the awarding of a PhD or equivalent research doctorate. Applicants must be current holders of a PhD
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sponsorship for the duration of the course through Research Training Program (RTP) Amount: 100% fee remission and up to $120,400 Duration: One or more years Quantity: 1 Eligibility and selection criteria