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, approximate inference, deep learning, or Bayesian optimisation are encouraged to apply. Interpretable Machine Learning for Natural Language – Led by Prof Lexing Xie, this stream applies machine learning
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 34 minutes ago
Learning for Natural Language – Led by Prof Lexing Xie, this stream applies machine learning to climate, health, and environmental challenges. Strong candidates will have experience in ML algorithms, human
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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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independent and collaborative research, developing expertise that enhances decision-making frameworks and optimises reconciliation processes in real-world business settings. The project will be
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foundational AI research in Australia, focusing on areas such as natural language processing, computer vision, and machine learning. This role offers the opportunity to carry out cutting-edge research
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will be part of two closely related Australian Research Council projects (Discovery and Linkage) that are using natural history collections, environmental DNA and ecological models to reconstruct
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in NLP. Completed a PhD or equivalent qualification or research experience in machine learning, natural language processing and image processing. Emerging track record and recognition for quality
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biology and biochemistry. Fluency in written and spoken English, with an ability to communicate scientific ideas to an expert audience. A strong work ethic, and the ability to work well independently, and
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until 30 June 2027 to contribute to the development of artificial intelligence systems which reliably and effectively detect anomalies in the workspace based on vision and/or natural language modalities
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with both academic and non-academic stakeholders. Capacity to manage research activities in coordination with Professor Cassey and the wider team of researchers at the Wildlife Crime Research Hub