627 proof-checking-postdoc-computer-science-logic positions at Monash University in Australia
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Remuneration: The successful applicant will receive a tax-free stipend, at the current value of $35,013 per annum 2024 full-time rate, as per the Monash Research Training Program (RTP) Stipend . Monash
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checks required for the role, as determined by the University. Enquiries: Professor Janet Anderson, Professor of Human Factors, janet.anderson@monash.edu Position Description: Research Fellow - Level A
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' for a confidential discussion. Your employment is contingent upon the satisfactory completion of all pre-employment and/or background checks required for the role, as determined by the University
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We are living in the era of the 4th industrial revolution through the use of cyber physical systems. Data Science has revolutionised the way we do things, including our practice in healthcare
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David Shugg Professionalism Scholarship Industry Leaders Scholarship This Scholarship is to honour the important role that David Shugg played in the professionalism of paramedics. Throughout David’s career, he advanced and embedded professionalism in paramedic training and education in the...
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, computing, manuscript preparation, and problem-solving skills. They should be well-organized, able to prioritize tasks, and communicate effectively. Proficiency in analyzing and interpreting meteorological
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., Pan, S., Aggarwal, C., & Salehi, M. (2022). Deep learning for time series anomaly detection: A survey. ACM Computing Surveys.
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We are excited to offer a fully funded PhD position at the Faculty of Engineering, Monash University (Australia). This project focuses on developing new algorithms to equip social robots with
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Planning is the reasoning side of acting in Artificial Intelligence. Planning automates the selection and the organisation of actions to reach desired states of the world as best as possible. For many real-world planning problems however, it is difficult to obtain the full model of the world...
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This PhD project is part of a larger project that aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain ML predictions and their uncertainty to different stakeholders, and evaluate the effect of the...