21 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions at University of Adelaide in Australia
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Educational Technology in the School of Computer and Mathematical Sciences. The successful candidate will be a researcher in the use of technology to support cognitive and meta-cognitive skills of students
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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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or nearly completed PhD graduate with experience in protein biochemistry to join the Herbicide and Antimicrobial Innovation Laboratory led by ARC Future Fellow Dr Tatiana Soares da Costa. Working
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an impactful career in quantum technology within a world-leading research institution. To be successful at Level A you will need: A PhD in Quantum Physics, good knowledge in the Physics of Quantum devices
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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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under farming systems including herbicide resistance and changes in emergence patterns. This role is ideal for a candidate with a PhD in Weed Science, Plant Genetics, or a related discipline, who is