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in the research Project, according to the University’s policies, practices and standards. The research program will specifically focus on 3-year ARC-funded project related to a novel gut-brain circuit
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and wellness discounts – fitness passport access, free yearly flu vaccinations, discounted health insurance, and access to our Employee Assistance Program for staff and their immediate family Career
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their knowledge and network within the resources industry. Mentor program Scholars are matched with an industry mentor tailored to their talents, aptitude, and interests, valued at $5,000. Annual cash grant
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flu vaccinations, discounted health insurance, and access to our Employee Assistance Program for staff and their immediate family Career development opportunities –access to exclusive internal-only
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Employment Type: Full Time Permanent Remuneration: $113926 + 17% super (level 7) Location: Kensington UNSW Campus (hybrid) Why Your Role Matters The Change and Training Analyst (Student Systems) supports the effective adoption and ongoing use of student systems through training, communication,...
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and exploiting IP assets. Engaging with Research Program Leaders and technical staff in identifying, developing, protecting and managing IP assets. Managing IP for the Energy sector, working with
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Employee Assistance Program for staff and their immediate family Career development opportunities –access to exclusive internal-only vacancies and our Study for Staff program On campus childcare options
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access to our Employee Assistance Program for staff and their immediate family Career development opportunities –access to exclusive internal-only vacancies and our Study for Staff program On campus
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This PhD project is funded by a successful ARC Discovery Project grant: "Improving human reasoning with causal Bayesian networks: a user-centric, multimodal, interactive approach" and the successful applicant will work as part of a larger research team. Reasoning and decision making under...
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Anomaly detection is an important task in data mining. Traditionally most of the anomaly detection algorithms have been designed for ‘static’ datasets, in which all the observations are available at one time. In non-stationary environments on the other hand, the same algorithms cannot be applied...