396 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "University of St" "St" "St" positions at Monash University in Australia
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career trajectories. The goal is to design better incentives for scientists to produce their best work. Our research group studies how groups of agents can learn to cooperate. Most of our research focuses
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FIT Indigenous Industry Based Learning Scholarship Sir John Monash Scholarship for Excellence Indigenous students enrolling in an undergraduate Information Technology degree at Monash University
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Background and Motivation Modern deep learning models have achieved remarkable success in computer vision and natural language processing. However, they typically produce overconfident predictions
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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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programming skills and a good background in maths. This project would set you up for a follow-up honours project in this area. https://github.com/cormackikkert/CEGARBox https://github.com/cormackikkert
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This project aims to develop robust algorithms capable of identifying and analyzing fingertips extracted from both static images and video footage. Machine learning techniques, particularly computer
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new x-ray imaging techniques from the synchrotron to the laboratory Transforming breast cancer imaging with x-ray phase contrast Webpage: https://xrayimagingmonash.wordpress.com/ For further details
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financial, personal, and confidential information. This project seeks to introduce machine learning and artificial intelligence techniques to effectively detect phishing websites. By leveraging these advanced
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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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, Farshid, Global Temperatures and Greenhouse Gases: A Common Features Approach (September 30, 2019). Available at SSRN: https://ssrn.com/abstract=3461418 or http://dx.doi.org/10.2139/ssrn.3461418 Fitzgibbon