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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 16 days ago
, spatial computing, computational creativity, text encoding, social media analysis, corpus linguistics, statistical analysis, web development. Confidence with at least one programming language is essential
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, monitoring workflow and in managing resources to meet objectives, timelines and deadlines. Excellent oral and written English language skills and a demonstrated ability to communicate and interact effectively
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processing. High level written and oral communication skills with the ability to represent the research team effectively internally and externally, including the presentation of research outcomes at national
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: A PhD in Mathematics, Computer Science, Engineering or other Machine Learning-related field. Programming experience in MATLAB, Python, C++ or other relevant language and experience in deep neural
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 18 days ago
, corpus linguistics, statistical analysis, web development. Confidence with at least one programming language is essential. The successful candidate will: Build their technical capability in one or more
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for Health Economics is seeking a Level A Research Fellow to play a key role in an ongoing research program examining the effectiveness and cost-effectiveness of behavioural interventions, with a particular
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and leadership Demonstrated advanced programming skills in Python and R (including frameworks such as PyTorch and TensorFlow). Experience using/applying advanced AI techniques including large language
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experience in machine learning research and development, particularly with a specialisation in such areas as: digital forensics, computer vision, biometrics (face or voice recognition, etc.) and natural language
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government and industries in South Australia, and overseeing Centre performance. The appointee will also be supported to establish and build a dynamic research program in machine learning or artificial
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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