16 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions at University of Adelaide
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computer vision and machine learning research group in Australia -- and contribute to world-leading research projects at the CommBank Centre for Foundational AI This postdoctoral research position is part of
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collaboration between industry, government, and academia. The Australian Institute for Machine Learning (AIML) at the University of Adelaide is the largest computer vision and machine learning research group in
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the direction of A/Prof Claudia Szabo in the School of Computer and Mathematical Sciences at the University of Adelaide. The project is a collaboration with Defence Science and Technology Group, within the Combat
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This PhD scholarship is funded by an Australian Research Council Industry Fellowship grant. It is a 3.5-year research training program. The ARC Industry Fellowship program aims to develop a strong
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technologies, with a specific focus on electrode/electrolyte interface studies for secondary batteries. The successful candidate will have recently completed, or be nearing completion of, a PhD in a relevant
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the timing, scale, and rate of mammal declines in Australia. They will use critical inferences of past demographic change and high-performance computing to disentangle the ecological mechanisms that were
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responders and operational risk assessment regarding skin decontamination and will build on a program of work focused on dermal exposure to chemicals. To be successful you will need: Completion of a PhD in
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Wildlife Crime Research Hub as part of the ARC Industry Laureate Fellowship program, Combatting Wildlife Crime and Preventing Environmental Harm at one of Australia’s leading research institutions
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to engage and collaborate with the broader University, school and discipline group to establish collaborative multi-disciplinary research outcomes. Qualification/s: A PhD in Civil Engineering specialising in
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PhD in Economics is a desirable criterion, we will consider candidates currently completing a PhD in Economics or a related field (such as Statistics or Applied Data Science) and who have a strong