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of computer-based records systems/databases Relevant tertiary qualifications in finance or business with significant relevant experience and skills in management and current membership of the Institute
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collaboratively with colleagues, strong computer literacy with proficiency in Microsoft Office and relevant university systems, and the ability to learn new software as required. Experience working with schools
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The world is dynamic, in constant flux. However, machine learning typically learns static models from historical data. As the world changes, these models decline in performance, sometimes catastrophically so. This PhD will develop technologies for addressing this serious problem, building upon...
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Pro Vice-Chancellor (Researcher Development) Job No: 688391 Location: Clayton Campus Employment Type: Full-time, Fixed-term appointment Remuneration: A competitive remuneration package will apply Champion the next generation of researchers and research excellence at one of the world’s leading...
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Senior HR Adviser - Multiple Opportunities Job No.: 687663 Location: 211 Wellington Road, Mulgrave & Clayton campus Employment Type: Full-time and Part-time (0.6 FTE) opportunities Duration: Fixed-term appointments until 31 Dec 2026 Remuneration: $106,789 - $117,128 pa HEW Level 07 (plus 17%...
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the delivery of a range of technical services. This position manages electrical and electronic design and assembly, providing integrated solutions involving computer interfacing equipment and systems
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the Monash Engineering program. Am I eligible? You must be one of the following: An International student You must meet the following criteria: A commencing student enrolled or intending to enrol in
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Candidates should hold a previous degree (Bachelor’s and/or Master’s) in Computer Science, Data Science, Robotics, Mechatronics, or Software Engineering, with demonstrated knowledge in machine
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between theoretical and computational high-energy physics. The research contributes to the world-leading PYTHIA Monte Carlo Event Generator, which serves as the baseline for the majority of experimental
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Time series are an ever growing form of data, generated by numerous types of sensors and automated processes. However, machine learning and deep learning methods for analysing time series are much less advanced than for other forms of data. Our research is revolutionising the analysis of time...