644 assistant-professor-computer-science "https:" "https:" "https:" "https:" "https:" "Dr" positions at Monash University in Australia
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the research outcomes, skilled workforce, technology and partnerships to improve human health locally and globally. Supervisory team The principal supervisor will be Professor Danielle Mazza AM FAHMS . Professor
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learning? The Department of Banking & Finance in the Faculty of Business and Economics invites applications for sessional academics to join our dynamic academic team, with a primary focus on undertaking
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offers a unique opportunity to contribute to the growth of emerging research excellence in nursing, while primarily supporting Associate Professor Innes and Associate Professor Jones in key research
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for the role, as determined by the University. Enquiries: Associate Professor Bernhard Mueller, School of Physics and Astronomy, Faculty of Science, bernhard.mueller@monash.edu Position Description: Research
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the satisfactory completion of all pre-employment and/or background checks required for the role, as determined by the University. Enquiries: Dr Joanne Mouser, Student and Academic Services Manager, +61 3 9905 5428
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for the role, as determined by the University. Enquiries: Professor Mehmet Yuce, Electrical and Computer Systems Engineering Position Description: Research Fellow Applications Close:Monday 13 April 2026, 11:55pm
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the ARC Discovery Project “Designing Dignity: Civic equity through public bathroom architecture” funded by the Australian Research Council Discovery Project awarded to Professor Nicole Kalms and Professor
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discover them The Opportunity The Department of Electrical and Computer Systems Engineering at Monash University is seeking a motivated Level A Research Fellow for a 2 year research-only appointment. A Level
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teaching and inspiring future marketers? The Department of Marketing in the Faculty of Business and Economics invites applications from industry professionals to join our sessional teaching team
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analysis, contextual analysis, audio feature extraction, and machine learning models to identify and assess potentially dangerous content. Similarly, computer vision models are implemented to analyse images