632 assistant-professor-computer-science "https:" "https:" "https:" "https:" "Kyoto university" positions at Monash University
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. Working under the guidance of the Professor of the area, the role helps coordinate codesign activities, develop bespoke materials and surveys, and assist with data collection, analysis, and research
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infancy is difficult. This PhD program aims at using state-of-the art multi-channel near infrared spectroscopy (NIRS) to assess the functional brain response of infants born preterm in long-term follow-up
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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 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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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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of Social Sciences is seeking a Level B research-only candidate to undertake independent and collaborative research within a multidisciplinary project, Empowering households in resource-efficient
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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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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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for up to three training scholarships in health economics within the PACE program. The successful candidates will undertake a tailored training program in theory and methods relevant to WP-1 or WP-2
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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