432 phd-studenship-in-computer-vision-and-machine-learning PhD positions in Australia
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at an Australian university; hold an appropriate visa to study in Australia (if international); be no further than one year (FTE) into a PhD candidature on commencing at CSIRO; hold a primary scholarship; for
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Scholarships are open to domestic or international students. The successful applicant must have already applied for, or have already commenced a PhD research program at RMIT and accept Data61 scholarship
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the following knowledge and/or experience are highly preferred: Computer Vision, Signal Processing, Machine Learning knowledge and/or; Experience Industry knowledge and/or; A track record of published
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UniSQ is offering a number of stipend (living allowance) scholarships for domestic students studying, or commencing the Doctor of Philosophy (PhD) in 2025. Applications in all areas of research
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maximum of 3 years Supervisor: N/A Available to: Domestic and International students PhD Eligibility Criteria To be eligible to apply for this scholarship, applicants must: Be enrolled in a PhD program at
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team tackling major challenges facing the world’s population in global sustainability and wellbeing as part of the QUEX Institute. The joint PhD programme provides a fantastic opportunity for the most
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product to benefit society and the environment. The group's Digitalisation and Computation Stream is led by Dr Camilo Cruz Gambardella who is developing new understandings of AI and Machine Learning tools
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team tackling major challenges facing the world’s population in global sustainability and wellbeing as part of the QUEX Institute. The joint PhD programme provides a fantastic opportunity for the most
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teaching assistance work. Application closing date: 2 March 2025 (for commencement in July 2025). Current opportunities As a candidate in the CHE Integrated PhD Program , you will receive rigorous training
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@rmit.edu.au Dr. Shao, Wei (Data61, Marsfield) - wei.shao@data61.csiro.au The successful candidate is expected to have strong motivation and evidenced skills in machine learning and computer vision