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Scholarship code: SRS-25032 This scholarship has been established thanks to the generosity and vision of the late Mr Anastassios Vassilogianis, benefactor of La Trobe University's Greek Studies program. It is a testament to his desire to support Hellenic studies and research for and by students...
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Status: Closed Applications open: 1/09/2024 Applications close: 30/09/2024 View printable version [.pdf] About this scholarship Description/Applicant information The MRIWA Odwyn Jones PhD
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PhD Scholarship Opportunities in Optoelectronic Semiconductors at the Faculty of Engineering and Faculty of Science (Multiple Positions) Job No.: 682543 Location: Clayton campus Employment Type
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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 a top-up to
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. The candidate will work closely with the CIs, post doc and PhD (machine learning) candidate, to develop choreographic structures used to generate movement and interaction capabilities that will define human-robot
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requirements for a Doctor of Philosophy (PhD) at QUT, including any English language requirements for international students. You must also enrol as a full-time, internal student. Applicants will be assessed
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The University of Adelaide and leading orthopaedic device manufacturer Austofix invite applications for two PhD projects, exploring Proximal Femoral Nailing for hip fracture patients About Austofix
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and hands-on experience with AI and computer vision. Solid programming skills in Python, especially with PyTorch. Practical experience with deep learning projects, including working with attention
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commenced a PhD, the term of scholarship will be reduced by the period of study already undertaken. Scholarships include learning and development expenses of up to $5,000 over the term of scholarship with
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university research into commercial outcomes. Under this program, PhD students will gain unique skills to focus on impact-driven research. This Project aims to develop a predictive machine learning model