201 phd-computer-science-"IMPRS-ML"-"IMPRS-ML"-"IMPRS-ML" positions at University of Adelaide
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Job no:516981 Work type:Continuing - Full-time Campus:Roseworthy Categories:Technical, Laboratory and Research Support, Faculty of Sciences, Engineering and Technology (HE05/6) $76,429 - $99,929 per
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This PhD research scholarship (Learning Lessons from Drug Resistance to Tackle Herbicide Resistance) is funded by the Australian Research Council to support a full-time PhD student to undertake
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These scholarships are funded by the Australian Research Council (3) and the University of Adelaide (1) to support 4 full-time PhD students who are undertaking research in the field of battery
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platform for conducting impactful economic research. To be successful you will need: PhD in applied economics, forensic accounting, ecological economics, criminology or a related discipline. Demonstrated
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of Humanities Faculty of Arts, Business, Law and Education / School of Social Sciences Eligibility: The PhD student must be: within the first 18 months of their candidature, willing to undertake the research
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-leading research and teaching. Why Join Us? The University is the third-oldest university and a member of the prestigious Group of Eight (Go8). Our Engineering program is ranked 46th in the world in
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, CSIRO, Curtin University of Technology, Geoscience Australia, the Minerals Council of Australia, New South Wales Department of Primary Industries, Primary Industries and Resources South Australia and the
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PhD in Computer Science, Engineering or other Machine Learning-related field. • Programming experience in python, C++ or other relevant language and experience in deep neural networks • Strong
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their Master's degrees in AI and machine learning. Join AIML's research community and contribute to shaping the future of industrial AI. This innovative program is supported by the South Australian Government
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, contributing to ground-breaking discoveries with real-world implications for cancer patients. To be successful you will need: A PhD in (awarded or near completion) in Computational Biology, Computer Science