561 computer-science-"https:"-"ESPCI-Paris---PSL" "https:" "UCL" positions at Monash University
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, software, human-computer interaction, ...). We also work very much interdisciplinarily with colleagues from other faculties, e.g. on bio-diversity matters, on physical aspects, on modelling aspects, and on
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Clinical Innovation and Informatics Stream Coordinator Job No.: 686703 Location: 553 St Kilda Road, Melbourne Employment Type: Part-time, fraction (0.6) Duration: 12 month fixed-term appointment
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Lecturer (Education Focused) - Electrical and Computer Systems Engineering Job No.: 688449 Location: Clayton campus Employment Type: Full-time Duration: Continuing appointment Remuneration: $118,974
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find some of our publications here: https://i.giwebb.com/research/computational-biology/ Required knowledge A solid grounding in artificial intelligence and machine learning. Learn more about minimum
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cooperating with each other, but in many cases competing for individual gains. This structure may not always work for the benefit of science. The purpose of this project is to use game theory and computational
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Lecturer/ Senior Lecturer - Electrical and Computer Systems Engineering Job No.: 688022 Location: Clayton campus Employment Type: Full-time Duration: Continuing appointment Remuneration: $114,951
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enjoy my learning experience in 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
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surrounded by extraordinary ideas - and the people who discover them The Opportunity The Faculty of Engineering – Joint Departments of Electrical & Computer Systems Engineering and Mechanical & Aerospace
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Cabrini/Monash Nursing and Midwifery PhD Scholarship Program – The Peter Meese Cabrini Oncology Nursing PhD Scholarship Job No.: 690199 Location: To be confirmed (Clayton/Malvern) Employment Type
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background in AI/ML, data science, or signal processing Interest in music informatics, emotion modelling, or multimodal AI Ability to implement and evaluate machine learning models independently Commitment