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models (eg auto-encoders and generative adversarial networks) and reinforcement/imitation learning algorithms for Markov Decision Processes. The application areas are different problems in text processing
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designing and implementing new algorithms to produce visual aids to assist people to reason with causal Bayesian networks, as well as the planning and conduct of exploratory usability studies to assess
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distributions. We wish to represent the biological networks into proper formats, e.g., vector representations, so that existing machine learning algorithms (e.g., support vector machines) can readily be used
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capability. Collaborate & Develop: Work with the other key teams in the Enterprise Engineering group to develop standard and bespoke solutions to meet unique business objectives. Lead Major Change: Manage the
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the School’s Master course in Food Science and Agribusiness. The successful candidate will be responsible for unit coordination, the development and delivery of content, supervision of discipline-specific
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candidate you will have: Highly developed numeracy, analytical and conceptual skills including the ability to quickly assimilate new concepts and information and deliver innovative solutions Superior
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complex administrative or technical functions and business systems involving significant resources Lead and develop a high-performing team with a strong customer focus Foster continuous improvement in
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, and will provide expert advice and analysis to support Monash’s regulatory obligations, including preparing institutional submissions, coordinating audit responses, and developing strategies to maintain
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). We’re offering an exciting opportunity for a Level A Research Assistant who will contribute to the University’s research efforts and develop their scientific expertise through focused and meaningful
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advice and in-depth analysis of complex health data. The role supports both independent and team-based research activities, including the development of manuscripts, conference presentations and funding