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to practice-oriented learning. UTS Law seeks to develop partnerships with external stakeholders to meet the rapidly changing needs of the workforce and to address issues of social justice. Reporting to the Vice
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to contribute to the development of innovative machine learning solutions using deep learning and multimodal foundation models. Working closely with leading researchers, you will design, develop, and implement
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, administrative, and facilities- based support to assist teaching staff and students to achieve teaching, learning and research outcomes associated with the Rural Health School. Skills and Experience To be
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of the university’s largest schools, with a rapidly expanding teaching and research portfolio. The School is at the forefront of emerging fields, including Artificial Intelligence, Machine Learning, Quantum
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, Technology and Information in Human-Computer Interaction (HCI), with a focus on responsible computing. The successful candidate will have an interest in online safety, including areas such as social media
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Neutral Infrastructure (dfCO2), this role contributes to Program 4: Machine Learning for Carbon Performance (https://dfco2.org.au/program_4 ) that aims to advance the next‑generation AI methods to model
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focused on securing systems and addressing data privacy and security challenges in machine learning. About You To be successful for this position, you will have: Demonstrated ability to prepare and deliver
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Great benefits such as 17% Super, generous annual, personal and parental leave, Employee Assistance Program, Medical Hub on Campus,Novated Car Leasing, 25% discount on some short courses, personal
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into the School’s activities. We are particularly interested in candidates with expertise in Digital Health and AI in Medicine, including machine learning (especially deep learning), natural language processing, and
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forecasting/uncertainty. Holger Maier is internationally recognised for developing and applying AI/machine learning, optimisation (notably evolutionary algorithms), and decision-support methods for complex