70 phd-studenship-in-computer-vision-and-machine-learning PhD positions at Curtin University
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research priority, leverage existing Australian investments, and provide computational and statistical training. Expected outcomes include advances in astrophysical knowledge, enhanced national and
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must enrol into a Doctor of Philosophy (PhD) program (full-time study). Eligibility criteria The successful candidate must meet the minimum academic entry requirement for admission into the Doctor
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an ARC DECRA project in conjunction with support from Curtin University. The purpose of this scholarship is to support a PhD student in researching proton batteries. Proton battery is a low-cost and safe
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benefits for patients and health care services. Aims To investigate the outcomes of a pharmacist-led antimicrobial stewardship (AMS) program that targets UTI management in Western Australian RACHs
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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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, (9) Industry, Innovation and Infrastructure, (11) Sustainable Cities and Communities and (12) Responsible Consumption and Production. The PhD will be conducted within the Hydrogen Storage research
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courses Any HDR student wishing to study in the exploration seismology filed. The successful candidate must enroll into a Doctor of Philosophy (PhD) program (full-time study mode). Eligibility criteria
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the spectrum of experience from PhD candidate, early career to senior academics. The candidate will experience industry networking with the non-government sector and policymakers (Department of Health WA) during
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, power, IT, or computer engineering students eligible to enroll in a PhD by research degree Eligibility criteria Full-time enrolment Successful recipient will collaborate with our industry partner in
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Status: Closed Applications open: 27/03/2025 Applications close: 27/04/2025 View printable version [.pdf] About this scholarship Description/Applicant information The PhD project, funded by