306 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" uni jobs at University of New South Wales in Australia
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to applied quantitative analysis and machine learning workflows that support infrastructure systems research and urban analytics. The role focuses on working with large-scale, structured, and geospatial
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basis for specific course(s). Please refer to the academic calendar in link for the exact dates: https://www.student.unsw.edu.au/calendar Please note that to be considered for this role you must have
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Apply now Job no:534992 Work type:Casual Location:Sydney, NSW Categories:Administration, Research Administration support Are you a detail-oriented Learning Designer with a passion for creating
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University of New South Wales | Canberra, Australian Capital Territory | Australia | about 15 hours ago
systems and applications including word processing, spreadsheets, presentations and demonstrated ability to learn new applications. Excellent time management skills, with a demonstrated ability to respond
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collaborating closely with industry and research partners. For further information, please visit: https://www.unsw.edu.au/engineering/our-schools/electrical-engineering-telecommunications Position Summary
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AI concepts, can build agentic systems, and are comfortable exploring new tools, frameworks, and platforms. They bring strong IT fundamentals, a learning mindset, and the enthusiasm to figure things
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to detail The ability to engage with a wide range of stakeholders and simplify complex information Initiative, adaptability and a willingness to learn quickly on the job The ability to work both
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, including the preparation of test plans, test cases and test reports. The role is expected to stay updated with and apply UNSW IT testing standards and guidelines and to learn and be proficient with the tools
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enable students to put into practice broad business content, enabling students to develop relevant business skills. Work-Integrated Learning (WIL) is a crucial component of a UNSW Business degree. Through
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on the benefits, please visit https://www.jobs.unsw.edu.au/lifestyle-benefits To Apply: If this is of interest to you, please submit your application online: CV, Cover Letter and responses to the Skills and