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Background Scholarship code: IND-25122 Expressions of interest - open until filled. This is an industry-linked PhD scholarship. This scholarship is created by La Trobe University in collaboration
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The Adelaide Graduate Research School (AGRS) and Hubble are partnering to create 2 remote internship opportunities for University of Adelaide PhD students, to contribute to various projects. Hubble
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Futures Institute are seeking motivated and qualified candidates for up to 15 fully-funded PhD scholarship. The preferred candidate should have strong programming and data science abilities, with
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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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Charles Sturt University | Charles Sturt University, New South Wales | Australia | about 2 months ago
https://www.csu.edu.au/scholarships/scholarships-grants/find-scholarship/research/csiro-acdp-csu-joint-phd-program might have a temporary problem or it could have moved. What can you do about it
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PhD. The duration includes an extension of up to six months (PhD) if approved for your candidature. This is the full-time, tax exempt rate which will index annually. You will also receive an additional
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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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. 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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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