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Code for the care and use of animals for scientific purposes (8th edition 2013 (updated 2021) (the Code)). The AEC is comprised of members across various categories as stipulated in the Code and includes
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processing, or autonomous driving. Proficient coding skills in Python, preferably with hands-on experience on deep learning frameworks such as PyTorch, TensorFlow, or Keras. Project funding Project based
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points required to complete your degree. Number offered Variable depending on funding Selection criteria Awarded on the basis of academic achievement and video application. Applicants must provide a video
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The number of placements offered varies depending on available funding. Selection criteria Based on academic achievement, application, video interview and performance at an interview with the host. To retain
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: Creating a multimedia submission (a short video or a photo journal) highlighting a memorable aspect of your experience or reflecting on what you gained from it overall; Assisting at University promotional
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as child exploitation material). It will involve the use of deep neural networks for image, video, audio, social network, and/or text classification. The Faculty of Information Technology has a mission
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with real-world application to pressing health challenges. In this role, you will: Develop new statistical methodology to support adaptive variants of cluster randomised trials Write R or Stata code
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of research and teaching activities involving animals to ensure the use of animals is justified and has scientific merit and animal welfare is prioritised, in accordance with the Australian Code for the care
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Code for the care and use of animals for scientific purposes (8th edition 2013 (updated 2021) (the Code)). The AEC is comprised of members across various categories as stipulated in the Code and includes
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Ensembles over Continuous Data", PETS 2022 - "Privacy-Preserving Video Classification with Convolutional Neural Networks", ICML 2021 - "Privacy-Preserving Feature Selection with Secure Multiparty Computation