457 professor-computer "https:" "https:" "https:" "https:" "https:" "Dr" positions at Monash University in Australia
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of anti-malarial agents has been a significant research area within the Faculty. Reporting to Professor Peter Scammells, the focus of the study will be the development of small molecule enzyme inhibitors
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the University. Enquiries: Professor Jenny Gamble, Professor of Midwifery, +61 3 9904 4640 Position Description: Senior Lecturer (Midwifery) Applications Close: Friday 20 February 2026,11:55pm AEDT Supporting a
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Goal Recognition is the task of inferring the goal of an agent from their action logs. Goal Recognition assumes these logs are collected by an independent process that is not controlled by the observer. Active Goal Recognition extends Goal Recognition by also assigning the data collection task...
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the different actors' beliefs and intentions. We will study the properties of such explanations, present algorithms for automatically computing them as well as extensions to existing frameworks and evaluate
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that occurs within these biological neural networks, so that these networks can be leveraged for AI applications. In addition, you will develop mathematical and computational neuroscience models
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Fellows to join a major program (>$20M) funded by the Advanced Research Projects Agency for Health (ARPA-H). This ambitious program focuses on lymphatic pathophysiology and the development of innovative
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contingent upon the satisfactory completion of all pre-employment and/or background checks required for the role, as determined by the University. Enquiries: Associate Professor Olivia Khoo, Head of Film and
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operators for these notions. Over the past fifty years, such non-classical logics have proved vital in computer science and logic-based artificial intelligence: after all, any intelligent agent must be able
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Master of Commerce Scholarship Sir John Monash Fee Scholarship The Master of Commerce is a research-oriented programme preparing students for a PhD and an academic career. Offered as part of
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., Pan, S., Aggarwal, C., & Salehi, M. (2022). Deep learning for time series anomaly detection: A survey. ACM Computing Surveys.