389 computer-programmer-"https:"-"https:"-"https:"-"NOVA.id" positions at Monash University
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classification'', Computer Journal, Vol 11, No 2, August 1968, pp 185-194 Wallace, C.S. and D.L. Dowe (1999a). Minimum Message Length and Kolmogorov Complexity, Computer Journal (special issue on Kolmogorov
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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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. Required knowledge Strong background in machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch
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methods dealing with model complexity - e.g., AIC, BIC, MDL, MML - can enhance deep learning. References: D. L. Dowe (2008a), "Foreword re C. S. Wallace", Computer Journal, Vol. 51, No. 5 (Sept. 2008
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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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supporting our mission. Headquartered at Monash University, the Centre is a transdisciplinary, multi-stakeholder program aiming to mobilise survivor-centric and Indigenous approaches, interdisciplinary
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be some flexibility as to the specific date of commencement. Enquiries You are required to discuss your research proposal with Dr Louise Devenish (Graduate Research Program Director), Sir Zelman Cowen
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across academia and industry. This position forms part of a major national program in Australian green ironmaking and will utilise Monash’s world-class analytical capabilities and pilot-scale facilities
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-powered tools for SE/PL, including program analysis, automated repair, and software testing is sought. Appointees will bring strong technical capability to collaborate with related groups in cybersecurity
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., Pan, S., Aggarwal, C., & Salehi, M. (2022). Deep learning for time series anomaly detection: A survey. ACM Computing Surveys.