31 computer-science-quantum-phd-student PhD positions at Queensland University of Technology
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for QUT's Doctor of Philosophy , including any English language requirements. Enrol as a full-time, internal student. Have a background in electrical, mechatronic, or biomedical engineering, expertise in
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supported by an ARC Industry Fellowship, in partnership with Bush Heritage Australia. The student will work closely with ecologists and computer scientists at QUT and conservation managers at Bush Heritage
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English language requirements enrol as a full time, internal student (unless approval for part-time and/or external study is obtained) a master’s or honours degree in Materials Engineering, Physics, or a related
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What you'll receive You'll receive a stipend of $33,637 per annum for a maximum duration of 3.5 years while undertaking a QUT PhD. The duration includes an extension of up to six months if approved
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project support scholarship. The student will still require the award of a research scholarship from QUT as part of their admission to the higher degree by research (HDR) program. Preference will be given
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prosper in careers in Australia’s data-skilled workforce. Our PhD scholarship program provides opportunities for outstanding postgraduate students with demonstrated academic and research excellence
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What you'll receive You will receive a living stipend scholarship of $33,637pa for a period of 3.5 years. This payment is indexed annually, and will be tax exempt for full-time students. In addition
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Application dates Applications close7 July 2025 What you'll receive For Master of Philosophy students, you'll receive: a top-up stipend scholarship of $10,000 in equal instalments. This is the full
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What you'll receive You will receive: a minimum of $30,000 per year, for 3 years a QUT tuition fee sponsorship (for international students). Eligibility You must: fulfil our PhD admission criteria
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) before the human eye can see them. The principal aim of this PhD research program is to develop methods to improve the hyperspectral image classification using deep learning techniques. The developed